1 00:00:00,000 --> 00:00:11,900 Happy to have you here. Got so many cool things to talk about. I've got a couple remarks about 2 00:00:11,900 --> 00:00:22,480 an interesting public meeting in Massachusetts that occurred yesterday before I groan on 3 00:00:22,480 --> 00:00:28,700 about all my thoughts. Candice, I know you listened in. Would you be interested in giving 4 00:00:28,700 --> 00:00:35,020 the group a lowdown of what people were talking about in Massachusetts yesterday and maybe 5 00:00:35,020 --> 00:00:39,560 your synopsis? Not to put you on the spot or anything, but you're welcome to share if 6 00:00:39,560 --> 00:00:49,400 you would like. Yes. So the meeting was held at, it was a joint committee on, at the Boston 7 00:00:49,400 --> 00:00:59,640 State House regarding cannabis policy. And they were asking for some data from the CCC. 8 00:00:59,640 --> 00:01:06,120 They were looking for averages, so pass, fail on like pesticides and microbes and what have 9 00:01:06,120 --> 00:01:14,360 you. Whereas I'm asking for absolute values of pesticides detected for every product 10 00:01:14,360 --> 00:01:19,840 sold in Massachusetts, such as what they do in Florida by supplying medical patients with 11 00:01:19,840 --> 00:01:28,760 the compliance reports that show probably 50 pesticide types and with absolute detection, 12 00:01:28,760 --> 00:01:35,320 not just meet state requirement pass fail. And another thing that they're trying to do 13 00:01:35,320 --> 00:01:43,220 too, is they're trying to eliminate vertical marketing so that it's easier for dispensaries 14 00:01:43,220 --> 00:01:50,480 that are recreational to become medical. And there are other items too on the bill. I'm 15 00:01:50,480 --> 00:01:56,240 really interested in the open data sets. And then also too, there are others that are interested 16 00:01:56,240 --> 00:02:04,600 as well. So it was really great that the conversation was opened up and there were other bills also, 17 00:02:04,600 --> 00:02:14,080 such as with medical and what have you. But I did not want to see a physician at every 18 00:02:14,080 --> 00:02:19,640 dispensary. So I'm really kind of hoping that maybe doesn't get pushed through. But I am 19 00:02:19,640 --> 00:02:26,840 pretty passionate about open data sets and that patients need to be aware of the pesticides, 20 00:02:26,840 --> 00:02:36,040 growth hormones, any type of non natural additives added. But it was great. I recorded it, but 21 00:02:36,040 --> 00:02:37,040 so did Keegan. 22 00:02:37,040 --> 00:02:42,600 There may even be a public recording online. So I'll point you all in the direction, but 23 00:02:42,600 --> 00:02:49,800 it was a real interesting discussion because, right, as Candice mentioned, and what has 24 00:02:49,800 --> 00:02:55,920 dominated a lot of the regulatory discussion is just market structure, which as an economist, 25 00:02:55,920 --> 00:03:02,600 I understand is really of utmost importance. That's kind of how the market shakes out. 26 00:03:02,600 --> 00:03:07,640 I'll need to read more in depth to give my two cents on that. And then of course, there's 27 00:03:07,640 --> 00:03:14,720 always some sometimes nitpicky safety regulations that people are talking about. And I think 28 00:03:14,720 --> 00:03:24,220 some are being discussed there. But the predominant discussion, I think, well, at least half and 29 00:03:24,220 --> 00:03:33,280 half was about open data or access to data. And Candice raised several good points there. 30 00:03:33,280 --> 00:03:38,920 Just to look at the glass half full real quick. One thing that we had mentioned in the past 31 00:03:38,920 --> 00:03:45,800 was, OK, everybody's talking quality control, quality control, quality control. What does 32 00:03:45,800 --> 00:03:54,360 that mean? And the people in the laboratory space, they're real big fans of proficiency 33 00:03:54,360 --> 00:04:03,120 tests and accreditation. And why is that? Well, different reasons. But my personal belief 34 00:04:03,120 --> 00:04:11,040 is, well, you know, if the laboratories aren't very scared of proficiency tests and accreditation, 35 00:04:11,040 --> 00:04:17,720 then they must be, you know, that must be like a fairly maybe low bar to jump over. 36 00:04:17,720 --> 00:04:24,320 So that's my personal belief is, you know, most labs can pass a proficiency test. If 37 00:04:24,320 --> 00:04:29,360 you go through and check all the checkboxes, you can get accredited. So there's a lot of 38 00:04:29,360 --> 00:04:35,400 accredited labs out there. And there's a lot of proficiency testing. People are still complaining 39 00:04:35,400 --> 00:04:42,040 like, ah, there's still this kind of sticky issue with the laboratory space. And so we 40 00:04:42,040 --> 00:04:52,400 said, OK, well, we're quants here, right? We're data analysts, data scientists. So couldn't 41 00:04:52,400 --> 00:05:01,920 we try to quantify what quality control even means? And we took a stab at it a few months 42 00:05:01,920 --> 00:05:09,680 ago. And basically, the simplest thing that we could think of was, let's just look at 43 00:05:09,680 --> 00:05:17,280 the outcomes at the different laboratories. And then let's look at the averages and use 44 00:05:17,280 --> 00:05:23,240 statistics, right? See if any of these averages of outcomes are different. And so, of course, 45 00:05:23,240 --> 00:05:29,840 people are interested in how people are measuring THC and CBD. But we noticed, OK, there's a 46 00:05:29,840 --> 00:05:39,200 wide variety, wide variance in THC. It's pretty hard to conclude if anyone's statistically 47 00:05:39,200 --> 00:05:44,680 different on their THC average. So that's one thing. Then we started to look at, oh, 48 00:05:44,680 --> 00:05:52,360 maybe people are measuring contaminants differently, because as Candice was mentioning, that's 49 00:05:52,360 --> 00:06:00,200 of importance to particularly medical consumers. And then we started to just notice right off 50 00:06:00,200 --> 00:06:05,880 the bat, which is what you want to notice in statistics. You don't want to have to really 51 00:06:05,880 --> 00:06:10,400 pull it out. But we noticed that it looked like there were some structural differences 52 00:06:10,400 --> 00:06:18,200 with how people were measuring microbes and mycotoxins. I don't think there was a, I don't 53 00:06:18,200 --> 00:06:24,160 remember, actually, if we looked at this, lab by lab variance in pesticides or residual 54 00:06:24,160 --> 00:06:32,200 solvents. Either I don't remember a big variance there or we didn't look at it. But I know 55 00:06:32,200 --> 00:06:38,880 we specifically looked at microbe testing and people were testing differently, to the 56 00:06:38,880 --> 00:06:45,960 point where certain labs had really high failure rates and some had very low failure rates. 57 00:06:45,960 --> 00:06:51,640 And we even looked at licensees and we saw some licensees even had really high failure 58 00:06:51,640 --> 00:06:59,040 rates. Some north of 50%, I want to say. I think that was atypical. But you would run 59 00:06:59,040 --> 00:07:06,480 into some licensees that maybe had 30% failure rates or some like 60% or more. I think there 60 00:07:06,480 --> 00:07:11,760 were some that had like a 100% failure rate, but maybe they just sent in four samples. 61 00:07:11,760 --> 00:07:16,760 And like I said, that would be unfortunate for that licensee because if you sent in four 62 00:07:16,760 --> 00:07:23,560 samples, they all failed. You're going to be in a tough boat economically. We basically 63 00:07:23,560 --> 00:07:28,520 said that could basically be a measure of quality control. Just compare yourself to 64 00:07:28,520 --> 00:07:38,440 the average. So if you're a licensee and you're failing above average, then you may want to 65 00:07:38,440 --> 00:07:46,520 look at your facility and maybe ask some other people, try to find a consultant perhaps, 66 00:07:46,520 --> 00:07:53,020 and try to think about ways that you can maybe clean up your facility or lower your risk 67 00:07:53,020 --> 00:08:00,960 of failing. So that's on the licensee side. And then on the lab side, we said, okay, people 68 00:08:00,960 --> 00:08:05,760 are always talking about standardization. They want standardized results. So similar 69 00:08:05,760 --> 00:08:13,400 thing with microbe testing. So say you're screening for microbes. Maybe you notice another 70 00:08:13,400 --> 00:08:19,760 lab has a really low failure rate or a really high failure rate. Once again, maybe hire 71 00:08:19,760 --> 00:08:24,320 a consultant. Maybe you can call that laboratory up. They may not want to share their trade 72 00:08:24,320 --> 00:08:31,640 secrets or this or that, but you could start to investigate why. We're not saying anyone's 73 00:08:31,640 --> 00:08:38,640 doing anything wrong, but it's just a place to start to look. Maybe the people who have 74 00:08:38,640 --> 00:08:45,480 a really high failure rate for microbes aren't doing it correctly. Maybe they're getting 75 00:08:45,480 --> 00:08:53,560 a lot of false positives. Whereas maybe the people who are getting no detections, maybe 76 00:08:53,560 --> 00:08:59,200 they're actually the ones measuring it the most accurately. Maybe they're laser focusing 77 00:08:59,200 --> 00:09:09,360 it on a particular microbe. So we're not saying anyone's wrong from just having the outcomes 78 00:09:09,360 --> 00:09:15,920 they do, but we just thought, okay, that'd be an interesting place to just start looking. 79 00:09:15,920 --> 00:09:23,340 And the other thing too is that Florida is so transparent. 18,000 COAs they have on their 80 00:09:23,340 --> 00:09:29,360 dispensary websites for patients. Whereas Massachusetts, it took me four months to get 81 00:09:29,360 --> 00:09:36,000 the COAs for the cure relief product purchase. So that's another thing in my testimony too 82 00:09:36,000 --> 00:09:40,400 to the state house. Otherwise, sorry to interrupt. 83 00:09:40,400 --> 00:09:47,520 Well good point. And I'll do the other side of the glass real quick because I've got a 84 00:09:47,520 --> 00:09:57,440 couple of things about Florida. But the main takeaway is ask. So a lot of laboratories 85 00:09:57,440 --> 00:10:02,480 in the state have been asking for the data transparency. I think there is a couple of 86 00:10:02,480 --> 00:10:11,200 testimonials. I think one was maybe the CEO of MCR Labs. But various people spoke, some 87 00:10:11,200 --> 00:10:16,160 pro and some against. But as I said, it's good that the conversation's going there that 88 00:10:16,160 --> 00:10:26,560 you can at least ask. Candice did mention that ultimately these are just statistics. 89 00:10:26,560 --> 00:10:32,320 And so this now gets to the sticky and the interesting part. Once you get the statistics, 90 00:10:32,320 --> 00:10:35,320 things get controversial. 91 00:10:35,320 --> 00:10:41,060 But also too, I'm a medical patient in both states. And in Florida, I can get access to 92 00:10:41,060 --> 00:10:47,800 all the COA and compliance test information for pesticides and the other analytes. But 93 00:10:47,800 --> 00:10:54,920 in Massachusetts, I can't. So I'm really hoping that my testimony might add that medical spin 94 00:10:54,920 --> 00:11:03,000 that adds a snowbird, full transparency in Florida, no transparency really in Massachusetts. 95 00:11:03,000 --> 00:11:05,000 So I'm hopeful. 96 00:11:05,000 --> 00:11:11,600 I'll just quit dancing around the subject and just go ahead and get all my remarks out 97 00:11:11,600 --> 00:11:13,600 there. 98 00:11:13,600 --> 00:11:24,160 Massachusetts. The regulations for the public to see these statistics. Because that's sort 99 00:11:24,160 --> 00:11:38,240 of where the rubber meets the road, with just actually having the public or the move. In 100 00:11:38,240 --> 00:11:44,440 my opinion, the public are the movers and the shakers. Because the policymakers, the 101 00:11:44,440 --> 00:11:51,440 regulators, I think should already have access to these statistics. This bill is just for 102 00:11:51,440 --> 00:11:59,260 the public to see them. So I think the state, if they wanted to, they could already see 103 00:11:59,260 --> 00:12:06,200 if there's a discrepancy between failure rates from one lab to the other. But they don't 104 00:12:06,200 --> 00:12:14,900 have to do anything about it unless the public knows. So it's just like, so the regulators 105 00:12:14,900 --> 00:12:21,920 may know that one lab has a 0% failure rate and another lab has a 10% failure rate. But 106 00:12:21,920 --> 00:12:28,040 unless the public knows, they don't have to act on it. And so then it's basically as soon 107 00:12:28,040 --> 00:12:35,800 as the public knows that, hey, what's going on here? This lab's detecting microbes. This 108 00:12:35,800 --> 00:12:41,920 one's not. Then the regulators actually get their feet held to the fire. And then they 109 00:12:41,920 --> 00:12:50,520 actually have to go look at it. And then the laboratories, there was a really telling remark. 110 00:12:50,520 --> 00:13:01,400 One of the laboratory, maybe scientific officers spoke, and there was a really telling remark 111 00:13:01,400 --> 00:13:09,480 where they may be not paraphrasing correctly. So once again, double check the official record. 112 00:13:09,480 --> 00:13:15,760 But it was basically like, we have to be a little cautious about letting the public see 113 00:13:15,760 --> 00:13:23,180 the data because they may not understand it. And they may put a laboratory on blast, which 114 00:13:23,180 --> 00:13:30,840 is very scary. Well, that's sort of the point. We just mentioned that laboratories aren't 115 00:13:30,840 --> 00:13:41,200 scared of proficiency testing. They're not scared of accreditation. But maybe it's OK 116 00:13:41,200 --> 00:13:47,720 for laboratories to be a little scared that they may actually get called out if they're 117 00:13:47,720 --> 00:13:56,960 not testing properly. And I just think it's a little demeaning of the general public because 118 00:13:56,960 --> 00:14:07,520 I think a good way to go about life is to actually think of others as smart, super smart. 119 00:14:07,520 --> 00:14:14,080 In fact, I think it could even be in Dale Carnegie's, how to make friends and influence 120 00:14:14,080 --> 00:14:20,720 people. But you almost want to approach everyone as if they have something that they can share 121 00:14:20,720 --> 00:14:26,880 with you. They have some bit of knowledge out there. So there's tons of smart people 122 00:14:26,880 --> 00:14:32,640 in the general public. There's chemists, there's biologists. Just because they're not in the 123 00:14:32,640 --> 00:14:39,040 cannabis space doesn't necessarily mean they're not educated. And then it's also sort of like 124 00:14:39,040 --> 00:14:45,480 I talked about the panopticon approach. And I was trying to think of an analogy. And I'm 125 00:14:45,480 --> 00:14:54,400 sure there's better ones. But I was thinking about speeding. So if you knew, say, where 126 00:14:54,400 --> 00:15:03,360 every police officer was, well, then you just wouldn't speed near them. And you would just 127 00:15:03,360 --> 00:15:12,120 speed everywhere else. But the fact that there are some undercover cop cars here and there, 128 00:15:12,120 --> 00:15:21,120 you basically don't know which car is a potential police officer. So there may be no police 129 00:15:21,120 --> 00:15:28,600 officers on the road, but you just don't speed because you just never know who's looking. 130 00:15:28,600 --> 00:15:35,560 So it's not the best analogy. But it's a similar thing with lab results. Washington State, 131 00:15:35,560 --> 00:15:43,320 they're all public. Chances are, very few people are looking at these, right? We're 132 00:15:43,320 --> 00:15:49,600 looking at them, but scantily, right? I've only got so much time in my day. And so I 133 00:15:49,600 --> 00:15:55,720 only do like a really thorough look at the Washington lab results. I don't know, maybe 134 00:15:55,720 --> 00:16:00,880 once every few months, once a year. So I'm only doing a small look, but they don't know. 135 00:16:00,880 --> 00:16:07,400 They don't know who's looking. It could be Jim McCray, who I think has a company, Straightline 136 00:16:07,400 --> 00:16:14,040 Analytics, and he's been looking at these for a long time. Or maybe it's, you know, 137 00:16:14,040 --> 00:16:19,160 remember a good friend, Isaac, in Massachusetts, maybe he's looking at them, or Candace. So 138 00:16:19,160 --> 00:16:24,800 really anyone all over the world could be looking at these lab results. Maybe nobody 139 00:16:24,800 --> 00:16:32,920 is. But just the thought that, ooh, somebody could look at these and call me out if I'm 140 00:16:32,920 --> 00:16:42,400 not doing it properly. I think that puts the right incentive in place, where the laboratories, 141 00:16:42,400 --> 00:16:46,720 you know, they button up and they, you know, they follow the book, they do everything by 142 00:16:46,720 --> 00:16:52,600 their rules. Because, you know, who knows who's going to be looking at the certificate 143 00:16:52,600 --> 00:17:03,200 and nitpicking it. So, so anywho, let's get to the more fun stuff now, the actual data 144 00:17:03,200 --> 00:17:10,280 science. But I just kind of wanted to call to call this to your attention. Because once 145 00:17:10,280 --> 00:17:17,080 again, this bill may not go anywhere. So just be prepared for that. Because as I said, who 146 00:17:17,080 --> 00:17:23,600 is actually the one who's going to be held to the fire? It's really the regulators, right? 147 00:17:23,600 --> 00:17:30,360 Because they already have that data. This is just a bill for the public to be able to 148 00:17:30,360 --> 00:17:39,440 see that data. And so the regulators may not be thrilled about that. And so we'll see how 149 00:17:39,440 --> 00:17:47,960 things materialize. But we don't, as I said, the public are the movers and the shakers. 150 00:17:47,960 --> 00:17:55,720 So I'll show you basically how the public's moving the ball forward in Florida, and how 151 00:17:55,720 --> 00:18:05,520 there's still a little little room to go. So I'll just share with you real quick. Also, 152 00:18:05,520 --> 00:18:13,760 before I dive into this, I know I've been talking a long time. Robert, May or Rick, would 153 00:18:13,760 --> 00:18:20,160 you all want to chime in or have any thoughts on this? Well, I start to change gears a little 154 00:18:20,160 --> 00:18:21,160 bit. 155 00:18:21,160 --> 00:18:39,120 Yeah, one very brief thing is I looked at the the Washington lab results. And I mentioned 156 00:18:39,120 --> 00:18:49,640 that one technical item where the results column had a list of lists and I use Python 157 00:18:49,640 --> 00:18:59,000 and it took me literally or it took the computer a brand new laptop with the I nine to iterate 158 00:18:59,000 --> 00:19:09,280 through 10,000 records. It took almost 24 hours. So now I have like a million rows of 159 00:19:09,280 --> 00:19:19,140 of that lab result column that's been extracted into a proper database format. So I'll get 160 00:19:19,140 --> 00:19:24,840 either rest of it. But just as an interesting experiment, you know, it took me a while to 161 00:19:24,840 --> 00:19:32,280 loop through all of that. So it should be a lot of interesting data there. And, you 162 00:19:32,280 --> 00:19:38,160 know, so I'll mix it in with my data science classes. So it's good to have, you know, a 163 00:19:38,160 --> 00:19:44,280 second computer going while I'm study on the other stuff. So yeah, I'll get some good info 164 00:19:44,280 --> 00:19:48,200 to you real soon here. 165 00:19:48,200 --> 00:19:54,440 And I love it. So Robert's taking a look at these Washington lab results. And there's 166 00:19:54,440 --> 00:20:01,000 a lot of data there because it's basically every time a sample is sent into the laboratory, 167 00:20:01,000 --> 00:20:06,760 there's so many data points that are generated, right? It's getting screened for cannabinoids, 168 00:20:06,760 --> 00:20:14,360 potentially residual solvents, foreign matter, moisture, water activity, maybe micro toxins, 169 00:20:14,360 --> 00:20:22,400 microbes, and then pesticides. So, you know, between all of these, you could easily get 170 00:20:22,400 --> 00:20:28,880 close to 100 or maybe sometimes more than 100 analytes that were tested. And that's 171 00:20:28,880 --> 00:20:35,960 why I think this is such rich, valuable data that I think a lot of you awesome data scientists 172 00:20:35,960 --> 00:20:45,760 should look at, because there's a lot there. And I don't know, my first take is maybe we 173 00:20:45,760 --> 00:20:57,240 haven't fully understood all of this data. That's what we're after. But thank you for 174 00:20:57,240 --> 00:21:04,360 your noble work, Rick. Basically organizing, standardizing, and making the data accessible 175 00:21:04,360 --> 00:21:09,060 is what it's all about. So you did a lot of the hard work. However, now that you've got 176 00:21:09,060 --> 00:21:17,960 it in a nice, I think SQL table, hopefully you can start doing queries and start asking 177 00:21:17,960 --> 00:21:23,000 and answering interesting questions. Yep, definitely. 178 00:21:23,000 --> 00:21:35,240 Oh, well, on that note, let me share my screen with you and get you 1200 more messy laboratory 179 00:21:35,240 --> 00:21:43,800 samples. And you know, once again, that's probably, you know, north, we're close to 180 00:21:43,800 --> 00:21:56,200 10,000 or more analytes that were tested. Maybe a little shy of that, but I'm barely 181 00:21:56,200 --> 00:22:04,360 getting to it all. Okay. So speaking of lots and lots of data points, in say Florida, this 182 00:22:04,360 --> 00:22:17,960 is what you'd be looking to get. So if you purchased this Polifakush 8 produced by TrueLeave, 183 00:22:17,960 --> 00:22:22,000 I guess we don't know where this sold, but you know, one of the medical dispensaries 184 00:22:22,000 --> 00:22:30,440 in Florida, you'd want to try to get ahold of this as a good data steward. And as Candice 185 00:22:30,440 --> 00:22:39,320 mentioned, Candice is a medical patient in Florida, wouldn't mind, I think, right, trying 186 00:22:39,320 --> 00:22:45,920 to just track your consumption of cannabinoids. And also, ideally, you know, make sure you're 187 00:22:45,920 --> 00:22:53,240 not consuming any contaminants, or at least keeping your contaminant consumption to a 188 00:22:53,240 --> 00:23:00,360 minimum, right? You want to minimize that as much as possible. And we pointed out in 189 00:23:00,360 --> 00:23:08,680 previous meetups how flour in particular, but most cannabis products, I think edibles 190 00:23:08,680 --> 00:23:17,960 are the most stable, but even concentrates, there's a good amount of variability. But 191 00:23:17,960 --> 00:23:28,360 in this 8th, right, so this is 3.5 grams. So we've got milligrams per gram here. So 192 00:23:28,360 --> 00:23:34,920 actually, do I even have a script open here? Let's go ahead and open up a script here so 193 00:23:34,920 --> 00:23:42,120 we can start doing some interesting things while we talk about the data. The first one 194 00:23:42,120 --> 00:23:51,000 is just do a little bit of math, right? So what there is about 314 milligrams per gram 195 00:23:51,000 --> 00:24:06,680 of THCA, phenomenal. So that's, if you purchase this flour, you would be getting almost a 196 00:24:06,680 --> 00:24:16,240 little bit more than one gram of THCA. So we've mentioned in the past that, say you're trying 197 00:24:16,240 --> 00:24:23,440 to regulate your consumption of THCA, or maybe you're trying to regulate your consumption 198 00:24:23,440 --> 00:24:34,480 of CBG. Well, you'll have to basically do a little bit of math. Maybe you've got the 199 00:24:34,480 --> 00:24:45,840 set of scales or what have you. You can allot various portions of this. Or I'm just looking 200 00:24:45,840 --> 00:24:55,440 at daily consumption. So maybe you just want to trend over time. But regardless, the first 201 00:24:55,440 --> 00:25:01,360 step is just getting this data. So like I said, lots of cool things you can do with 202 00:25:01,360 --> 00:25:09,600 it or interesting and enlightening and helpful things that you can do with the data. But 203 00:25:09,600 --> 00:25:15,840 as I said, first things first, you need to get it. So in Florida, people have been asking 204 00:25:15,840 --> 00:25:23,000 for this a lot, a lot, a lot. And now they're starting to put QR codes right on the label. 205 00:25:23,000 --> 00:25:29,760 You scan the QR code. And ideally, you get this certificate. And why do you want this 206 00:25:29,760 --> 00:25:39,120 certificate? Because you've got the cannabinoids. Notice here real quick, terpene summary. So 207 00:25:39,120 --> 00:25:48,880 ideally, you actually want to scroll down here and get the full list of all the terpenes. 208 00:25:48,880 --> 00:26:00,560 Because remember, a non-detect is in fact a data point. Because, right, there was, for 209 00:26:00,560 --> 00:26:09,840 example, there was no, I think this is, you know, delta 3krin or alpha cedrine or alpha 210 00:26:09,840 --> 00:26:15,400 philandrine or alpha terpenine, right? That's an interesting one. I think you'd want to 211 00:26:15,400 --> 00:26:21,960 know that there's no alpha terpenine in this, right? So if you just look at the terpene 212 00:26:21,960 --> 00:26:30,280 summary, you know which terpenes are in it, but you don't know which ones weren't detected. 213 00:26:30,280 --> 00:26:41,040 So already, you gain a little bit of knowledge by knowing the non-detects. Because maybe 214 00:26:41,040 --> 00:26:46,760 they just didn't even test for alpha terpenine. Because then it may be in there, it may not 215 00:26:46,760 --> 00:26:53,240 be, they didn't test for it. So I think this will be useful data moving forward. Because 216 00:26:53,240 --> 00:26:59,360 as we're, well, as I'm kind of finding out like at these Canvas Science conferences and 217 00:26:59,360 --> 00:27:05,920 things, people are discovering more and more terpenes and, you know, which ones are significant 218 00:27:05,920 --> 00:27:15,520 and interesting to look for. So that's one thing. A data point that's, you know, worth 219 00:27:15,520 --> 00:27:23,560 writing down is the moisture content. Because there are scientists out there who think that 220 00:27:23,560 --> 00:27:32,960 if you were going to, and once again, I think there's, well, like I said, there are scientists 221 00:27:32,960 --> 00:27:38,680 who make the argument that, you know, if you're going to compare different flowers, it's pretty 222 00:27:38,680 --> 00:27:45,720 standard with botanical products to adjust for the moisture content. Because I think 223 00:27:45,720 --> 00:28:04,120 the idea is this 3.5 grams of Caliphakush is, where's that number, is 13.28% water. So, 224 00:28:04,120 --> 00:28:15,120 you know, of your 3.5 grams, is that right? You're going to be getting almost half a gram 225 00:28:15,120 --> 00:28:29,880 of water. That's what it is, right? It's a flower product. So, you know, so technically, 226 00:28:29,880 --> 00:28:43,480 I don't know. Once again, I need to think about this number more. But once again, it's 227 00:28:43,480 --> 00:28:49,280 worth jotting down because now you can at least know sort of the moisture content in 228 00:28:49,280 --> 00:28:57,440 your flower. Thought, comment, question? Yeah, I was just curious, the moisture content, 229 00:28:57,440 --> 00:29:05,200 if anyone knows if there are terpenes that could be lost due to evaporation, and so maybe 230 00:29:05,200 --> 00:29:10,840 that lower moisture content, that terpene wouldn't show up, a higher moisture content 231 00:29:10,840 --> 00:29:18,160 means that it was preserved. Does that make sense? I'm just trying to come up with a use 232 00:29:18,160 --> 00:29:24,880 case of where the moisture percentage would, we compare it with something else to maybe 233 00:29:24,880 --> 00:29:32,560 extract some insight. So, this may not be super reassuring, but from my understanding, 234 00:29:32,560 --> 00:29:44,080 some of these terpenes maybe are readily evaporating at room temperature. So, I think that's even 235 00:29:44,080 --> 00:29:50,760 like what gives cannabis its smell. So, if you, we'll talk about this momentarily, like 236 00:29:50,760 --> 00:29:56,000 someone had mentioned garlic, these garlic strains. From my understanding, you know, 237 00:29:56,000 --> 00:30:01,960 if you smell a really strong garlic strain and it's got a distinct smell, those are the 238 00:30:01,960 --> 00:30:09,840 actual terpenes. I forget what the correct word is, maybe aromatizing, but they're basically 239 00:30:09,840 --> 00:30:16,560 evaporating off of the plant and going up your nose in small amounts. So, I guess the 240 00:30:16,560 --> 00:30:21,160 way I picture it is like almost if you're holding a cannabis flower, you know, you can't 241 00:30:21,160 --> 00:30:26,640 see it, but I would imagine there's just almost just like fumes coming off of the flower, 242 00:30:26,640 --> 00:30:36,800 right? And so, like, you know, dogs can smell the cannabis flower. So, you almost, I guess, 243 00:30:36,800 --> 00:30:43,320 want to think about this as like a snapshot in time. So, it's like they got the flower, 244 00:30:43,320 --> 00:30:52,600 they got it to the lab, the second they extracted it, put it in the diluents, and maybe they 245 00:30:52,600 --> 00:30:58,360 put it in methanol or acetonitrile, or maybe it's just going straight onto the GC. So, 246 00:30:58,360 --> 00:31:02,600 it's just, which is just, from my understanding, I think you just put a little bit of flower 247 00:31:02,600 --> 00:31:07,720 in a little capsule, and then that basically just gets heated right onto the instrument. 248 00:31:07,720 --> 00:31:15,720 So, it's basically, so as to your question, like this actual percentage, I think is a 249 00:31:15,720 --> 00:31:22,280 little snapshot in time. And so, this is probably always going to be kind of diminishing as 250 00:31:22,280 --> 00:31:33,600 time goes on. Does water affect the rate this diminishes? I have no idea. I don't think 251 00:31:33,600 --> 00:31:40,680 like the terpenes would be like in the water themselves, right? The terpenes, I don't know 252 00:31:40,680 --> 00:31:48,280 where in the plant they actually are. They may be in the trichomes. But a hypothesis 253 00:31:48,280 --> 00:31:55,880 is that maybe this is a compact flower bud. Maybe if there's like moisture in there, like 254 00:31:55,880 --> 00:32:04,680 little H2O molecules in there, maybe that just prevents some of the terpenes from evaporating. 255 00:32:04,680 --> 00:32:09,580 But who knows? That's just pure conjecture. And so, that's actually a real interesting 256 00:32:09,580 --> 00:32:13,400 question and maybe room for some research. 257 00:32:13,400 --> 00:32:20,240 Yeah, definitely. The reason I asked is I had talked to some guys that had inside information 258 00:32:20,240 --> 00:32:26,960 on whether or not the moisture content affected THC levels in lab results. Now, this was a 259 00:32:26,960 --> 00:32:32,200 few years back, so this might not be the case anymore. But it seemed that there was kind 260 00:32:32,200 --> 00:32:39,360 of a golden area of moisture when submitting your flower that would yield better or higher 261 00:32:39,360 --> 00:32:45,480 THC results. So I was just curious if there was like something similar with the terpenes 262 00:32:45,480 --> 00:32:46,480 as well. 263 00:32:46,480 --> 00:32:58,240 But it could even be a quirk of the actual lab testing itself. Because it's a non-trivial 264 00:32:58,240 --> 00:33:05,400 thing to actually test cannabis flower because from my understanding, like the flower has 265 00:33:05,400 --> 00:33:15,280 a lot of like fats and lipids. And as we pointed out, it's got out of the 3.5 grams, you know, 266 00:33:15,280 --> 00:33:22,000 half a gram of water itself. So it's when you're testing this, you're basically just 267 00:33:22,000 --> 00:33:28,280 putting the whole concoction of the flower plant itself onto the scientific instrument. 268 00:33:28,280 --> 00:33:33,680 So I think there's techniques you can do to try to get rid of some of the fats and lipids 269 00:33:33,680 --> 00:33:43,480 and things. But it could almost just cause maybe inaccuracies in the testing, maybe. 270 00:33:43,480 --> 00:33:46,000 I don't know. 271 00:33:46,000 --> 00:33:56,000 So I didn't get a very scientific explanation from him. It was almost kind of like a wise 272 00:33:56,000 --> 00:34:01,800 tale type of a thing. But he believed that it worked and went by that. But he didn't 273 00:34:01,800 --> 00:34:06,480 have any actual data that he was looking at or anything. So yeah, like he said, it's an 274 00:34:06,480 --> 00:34:11,000 interesting point for research. So don't want to take us down any further down that rabbit 275 00:34:11,000 --> 00:34:15,560 hole. But yeah, I'll look into it and see if I find anything interesting. 276 00:34:15,560 --> 00:34:22,680 Please look into it, Rick, because obviously this was of importance to the producer, right? 277 00:34:22,680 --> 00:34:27,600 This was something they look for when they're trying to send their sample in for testing, 278 00:34:27,600 --> 00:34:34,760 which is pretty important to people. And so why it may work, it could be a couple factors. 279 00:34:34,760 --> 00:34:39,680 One, it could actually be something structural, right? Maybe there is something about the 280 00:34:39,680 --> 00:34:45,720 water and the turpines. And then there also could just be maybe there's some quirk in 281 00:34:45,720 --> 00:34:55,400 testing where maybe there's the way the labs calibrate their instruments. Maybe they can 282 00:34:55,400 --> 00:35:05,360 handle certain levels of moisture better than others. But anywho, as I said, the jury is 283 00:35:05,360 --> 00:35:11,520 still out. So that's why I get the data so that way you can do some statistics on it. 284 00:35:11,520 --> 00:35:16,960 And I always found this interesting because I actually tested moisture content in the 285 00:35:16,960 --> 00:35:30,600 laboratory and it can be quite variable. And it's one of the things that the analyst knows 286 00:35:30,600 --> 00:35:37,080 that, okay, this is going to be quite variable. And so the analyst takes into consideration 287 00:35:37,080 --> 00:35:45,280 that, okay, you may want to give a little bit of wiggle room to this 13.28% number, 288 00:35:45,280 --> 00:35:53,880 but the producers, they put so much faith into these numbers sometimes. And so sometimes 289 00:35:53,880 --> 00:36:01,240 that's where there's a little miscommunication, I think. Because maybe the producer is putting 290 00:36:01,240 --> 00:36:06,520 a lot of weight into the 13.28%, but from the laboratory's point of view, it's not 291 00:36:06,520 --> 00:36:14,400 really statistically different than the, say, 13% because they may have an internal laboratory 292 00:36:14,400 --> 00:36:22,080 margin of error. So anywho, that's a tiny little data point, but when you want to get... 293 00:36:22,080 --> 00:36:36,880 Let me let in a guest real quick. Oh, Hector's joining us. So anywho, want to get the moisture 294 00:36:36,880 --> 00:36:45,520 content? We'd like to go ahead and get the microbes and microtoxins. It's interesting 295 00:36:45,520 --> 00:36:52,720 kind of where I stand on these. Once again, you don't want moldy cannabis and that's, 296 00:36:52,720 --> 00:37:00,520 I think, definitely something you want to watch out for. Personally, I think... I don't 297 00:37:00,520 --> 00:37:07,120 know. I'm thinking the microbe screening is maybe going a little overboard, like a little 298 00:37:07,120 --> 00:37:15,560 overkill, because basically, from my understanding, microbes are just ubiquitous. I think they're 299 00:37:15,560 --> 00:37:24,760 on the table, they're on the food, they're in the air. So I think there's always maybe 300 00:37:24,760 --> 00:37:29,960 a small amount of them, but it's just like you don't want a lot of mold. So I think there's 301 00:37:29,960 --> 00:37:37,960 a give and a take. So I guess you can't be too stringent, maybe because you'll be kind 302 00:37:37,960 --> 00:37:49,360 of getting maybe like a false positive in the sense that it's maybe not like positively 303 00:37:49,360 --> 00:37:57,240 dangerous. But once again, I'm going to kind of defer this to some microbiologists and 304 00:37:57,240 --> 00:38:07,680 things. But I think it's at least looking at this data. But this is a landscape that's 305 00:38:07,680 --> 00:38:13,640 still developing because there's pretty strong stances on both sides. But as I said, the 306 00:38:13,640 --> 00:38:20,840 one thing that we can do is just get the data and then people can look at it. And then the 307 00:38:20,840 --> 00:38:29,760 final thing are the pesticides. And this is a data point that I feel pretty strongly about. 308 00:38:29,760 --> 00:38:38,280 I personally just am trying to avoid pesticides. I know they're out there. We talked about 309 00:38:38,280 --> 00:38:45,480 how these DDT breakdown chemicals are just still out there and they're just kind of hard 310 00:38:45,480 --> 00:38:53,920 to avoid. So I understand that there's maybe some background contamination here and there. 311 00:38:53,920 --> 00:39:03,680 So you just like to keep that to a minimum. The main thing is maybe somebody's spraying 312 00:39:03,680 --> 00:39:11,120 a lot of one of these pesticides and another producer's not. Personally, I don't know if 313 00:39:11,120 --> 00:39:18,360 these are permitted or completely banned. So in fact, I think even pesticide use in 314 00:39:18,360 --> 00:39:26,480 cannabis is maybe a contentious topic because some people feel that you're not even supposed 315 00:39:26,480 --> 00:39:36,520 to use pesticides because they made an argument that cannabis is such a gray area. But I think 316 00:39:36,520 --> 00:39:42,560 maybe the FDA may have to approve or maybe there's some regulatory body, maybe the Department 317 00:39:42,560 --> 00:39:47,880 of Agriculture. I don't know who does it, but I think somebody approves pesticides for 318 00:39:47,880 --> 00:39:54,840 use in various crops. So for example, I think the way they do this in Washington State is 319 00:39:54,840 --> 00:40:02,360 I think the Washington State Department of Agriculture has said that, okay, cannabis 320 00:40:02,360 --> 00:40:08,440 policies are approved to use this subset of pesticides. And so I don't know if they're 321 00:40:08,440 --> 00:40:12,600 allowed to technically use all of these or if maybe they're just screening for some of 322 00:40:12,600 --> 00:40:19,160 these for safety sake. So once again, that's sort of where my knowledge ends and then I 323 00:40:19,160 --> 00:40:24,640 encourage you to kind of do your own research to fill in the gaps. 324 00:40:24,640 --> 00:40:33,080 Okay, so why am I droning on about all these data points? Well, because Candice said that 325 00:40:33,080 --> 00:40:40,280 people have been asking for these. Well, one thing you have to look at the fine print for 326 00:40:40,280 --> 00:40:49,520 is this is a compliance test. So this was a test that was submitted to the state of 327 00:40:49,520 --> 00:40:58,880 Florida to say that the laboratory performed all of these tests. One thing I've noticed 328 00:40:58,880 --> 00:41:06,880 as we've gone about collecting these lab results is I keep seeing, and once again, this may 329 00:41:06,880 --> 00:41:13,680 be just a quirk of this one laboratory. However, I notice, and I don't know if they all use 330 00:41:13,680 --> 00:41:23,960 this language, however, I want to say I noticed at least three or four laboratories doing 331 00:41:23,960 --> 00:41:34,760 this practice where, look, this is the patient COA and it does say that it was tested for 332 00:41:34,760 --> 00:41:43,600 these contaminants and they do list the cannabinoids and the terpenes that were detected. 333 00:41:43,600 --> 00:42:00,080 But notice this. We don't have the results, right? All it says is pesticides were passed. 334 00:42:00,080 --> 00:42:09,480 You know, it says the moisture was passed, the microbes were passed, but we only have 335 00:42:09,480 --> 00:42:21,920 one page here. So unfortunately, this is sort of where, you know, we're not over yet. You 336 00:42:21,920 --> 00:42:31,080 know, the struggle to get lab results is not over because if, say, the laboratory submitted 337 00:42:31,080 --> 00:42:38,200 this COA to the state of Florida, I don't think the state of Florida would accept that. 338 00:42:38,200 --> 00:42:47,720 They would be like, great, but you're missing all the results. So this is, I think, sort 339 00:42:47,720 --> 00:42:54,120 of why people have described it, I think, in the Reddit forum is pulling teeth to get 340 00:42:54,120 --> 00:42:58,840 these lab results because it's just like, you know, the patients are like, we're demanding 341 00:42:58,840 --> 00:43:03,040 them like, come on, we want the lab results, we want the lab results, we want the lab results. 342 00:43:03,040 --> 00:43:10,800 And then they're like, okay, here are the lab results. But, you know, unless you're 343 00:43:10,800 --> 00:43:17,480 like, you really, you know, know your stuff about laboratory testing, you wouldn't really 344 00:43:17,480 --> 00:43:23,760 know right off the bat that this isn't in, from my understanding, you know, this isn't 345 00:43:23,760 --> 00:43:35,520 like the actual COA that was submitted to the state of Florida. From the look of this, 346 00:43:35,520 --> 00:43:44,800 this is once again, my conjecture and we're basically, there's like an advocate in Oregon, 347 00:43:44,800 --> 00:43:51,980 his big complaint is the laboratories at the end of the day, they make their money from 348 00:43:51,980 --> 00:44:02,520 selling this certificate or selling this analysis. And anyone who's in business knows that what 349 00:44:02,520 --> 00:44:10,920 do you do in business, you try to make your client happy. So people are pestering TrueLeave 350 00:44:10,920 --> 00:44:19,880 for lab results. TrueLeave notices, okay, you know, other companies. And once again, 351 00:44:19,880 --> 00:44:26,000 I don't want to pick on TrueLeave because here it actually is a full TrueLeave COA by 352 00:44:26,000 --> 00:44:33,200 ACS laboratory. So I don't know what exactly is going on here. And this one's even pretty 353 00:44:33,200 --> 00:44:41,240 recent. But like I said, I've seen this at other laboratories too. And so I'll point 354 00:44:41,240 --> 00:44:46,720 you in the direction of those COAs. And then I'll get on to some fun stuff here in a second. 355 00:44:46,720 --> 00:44:53,240 So I don't really want to pick on them for any reason. But my hypothesis of what may 356 00:44:53,240 --> 00:45:02,180 be going on here is people in Florida are asking for COAs. Some producers have started 357 00:45:02,180 --> 00:45:09,400 to provide those because there's pressure for them. Other producers want to provide 358 00:45:09,400 --> 00:45:20,960 them but they don't necessarily want to just show patients in Florida all of the contaminants 359 00:45:20,960 --> 00:45:31,480 because there may be a trace amount of abamectin or there may be a, this one doesn't see this 360 00:45:31,480 --> 00:45:39,080 is a clean green. This is what I would like to look for. But once again, you know, it 361 00:45:39,080 --> 00:45:45,560 may have a tiny minuscule amount of one of these pesticides, you know, it still passes 362 00:45:45,560 --> 00:45:51,280 and you know, that's okay. And you know, once again, patients may or may not care. But the 363 00:45:51,280 --> 00:45:57,840 point being is, I don't think there's like a law in Florida that says that you have to 364 00:45:57,840 --> 00:46:04,040 provide this to patients. And so what it looks like to me is they're kind of trying to pass 365 00:46:04,040 --> 00:46:15,920 this off as the official COA, because it kind of satisfies what the consumers are after 366 00:46:15,920 --> 00:46:23,240 because most people they just want to know the cannabinoids in the top terpenes. So this 367 00:46:23,240 --> 00:46:31,080 is phenomenal. So as I said, on the glass half full side, I'll take it right. I've said 368 00:46:31,080 --> 00:46:37,920 in the past, any data is better than no data. So you know, bravo for, you know, at least 369 00:46:37,920 --> 00:46:45,560 providing us with you know, the cannabinoid and the terpene summary. Thought comment question? 370 00:46:45,560 --> 00:46:51,520 It's Hector. Does the fact that cannabis is illegal federally cause problems on improving 371 00:46:51,520 --> 00:47:02,560 the pesticides? Yes. It's a gray area. Someone in Oregon who was a organic farmer, so you 372 00:47:02,560 --> 00:47:09,000 know, they're clearly biased towards no pesticides. But they made the argument that because it's 373 00:47:09,000 --> 00:47:14,360 federally illegal, like I said, I forget what the accrediting body is, if it's the FDA or 374 00:47:14,360 --> 00:47:19,360 the Department of Agriculture, I think it's probably one of those, but it could be another. 375 00:47:19,360 --> 00:47:26,000 They basically approve certain pesticides for various crops. And from my understanding, 376 00:47:26,000 --> 00:47:31,960 it's not approved by them, you know, you're not allowed to use it. I think basically, 377 00:47:31,960 --> 00:47:38,320 you know, just like cannabis, right, cannabis is not federally permitted. Certain states 378 00:47:38,320 --> 00:47:45,080 like Washington have stepped in to say, at a state level, our state is permitting it. 379 00:47:45,080 --> 00:47:52,120 So in Washington, I think they say, okay, we're permitting licenses to use these pesticides. 380 00:47:52,120 --> 00:47:59,640 So once again, the state may permit them to use the pesticides. Technically, the FDA or 381 00:47:59,640 --> 00:48:05,840 maybe the USDA could maybe go make a fuss about it. I don't think they've done that 382 00:48:05,840 --> 00:48:15,280 from my understanding, but they may. Once again, it'd be a whole can of worms and I doubt 383 00:48:15,280 --> 00:48:21,200 like any regulator wants to step in that. But from my understanding, people are using 384 00:48:21,200 --> 00:48:28,520 pesticides. But as you pointed out, Hector, it's not clear if it's just like cannabis 385 00:48:28,520 --> 00:48:31,520 itself, you know, it's not really clear if it's permitted. 386 00:48:31,520 --> 00:48:40,680 Thank you. But anywho, like I said, I think it's important to see the data. Because it's 387 00:48:40,680 --> 00:48:45,360 like pulling teeth, you know, the companies realize, okay, you know, we can we can let 388 00:48:45,360 --> 00:48:50,600 people know the cannabinoids and terpenes without that affecting our bottom dollar. 389 00:48:50,600 --> 00:48:57,160 And in some cases, you know, may actually be a marketing tool. But it still seems that, 390 00:48:57,160 --> 00:49:04,280 you know, the producers and and via the producers, maybe the laboratories themselves, because 391 00:49:04,280 --> 00:49:09,120 at the end of the day, you know, like, I don't want to say that this is the case, I'm trying 392 00:49:09,120 --> 00:49:14,800 to be careful with this, but could be that maybe the producer said, Hey, could you make 393 00:49:14,800 --> 00:49:22,640 us a COA that just has the cannabinoids and terpenes and the overall status and the labs 394 00:49:22,640 --> 00:49:27,360 like, Yeah, sure, we can do that. It's not breaking any rules. We'll still submit this 395 00:49:27,360 --> 00:49:34,800 compliance test to the state. And then you can show your patients this COA. Once again, 396 00:49:34,800 --> 00:49:42,440 it may be perfectly by the book. But in my opinion, like Candice said at the very beginning, 397 00:49:42,440 --> 00:49:52,200 I think you should be able to see a very granular breakdown of what's in your products. So I 398 00:49:52,200 --> 00:50:01,920 think you should be able to get this full COA. Some cases you can. And once again, it's 399 00:50:01,920 --> 00:50:10,920 sort of the panopticon approach. Maybe nobody ends up looking at your pesticide screening. 400 00:50:10,920 --> 00:50:18,680 But just the fact that they can look at it will make you check all your, you know, dot 401 00:50:18,680 --> 00:50:22,840 all your I's cross all your T's make sure you're doing everything by the book, because 402 00:50:22,840 --> 00:50:33,840 maybe nobody's looking. But you know, maybe maybe they will check. So once again, I so 403 00:50:33,840 --> 00:50:39,960 so just to go ahead and just show you, you know, a little data with with the time that's 404 00:50:39,960 --> 00:50:48,240 left. And then maybe I'll actually save, save some of it for next week since since we only 405 00:50:48,240 --> 00:50:54,200 have like five minutes left, I don't want to rush through it all. And it's too much 406 00:50:54,200 --> 00:50:58,760 cool, good material. So I'll post it all to GitHub. So that way, maybe you could look 407 00:50:58,760 --> 00:51:09,960 at it over the next week, because I've got some cool open AI, API queries that we can 408 00:51:09,960 --> 00:51:16,120 do. But they're, they're not really on topic with what we were doing today. So I can at 409 00:51:16,120 --> 00:51:20,240 least show you these Florida lab results, since that's what we were actually talking 410 00:51:20,240 --> 00:51:29,520 about. And so once again, this is the most recent, actually, probably the most recent 411 00:51:29,520 --> 00:51:36,640 ones one at the top. And this is just the most recent observation I've collected from 412 00:51:36,640 --> 00:51:46,800 Florida. And if any of you're interested, you know, can lytics has been writing these 413 00:51:46,800 --> 00:52:01,360 coa parsing algorithms. And we recently started with Florida. And written in out a crude algorithm 414 00:52:01,360 --> 00:52:14,080 for Keisha labs. And see Keisha, and then one for ACS laboratories. This Oh, yeah, I 415 00:52:14,080 --> 00:52:27,320 don't have many. So here's a cake face flower. And you know, we're just collecting various 416 00:52:27,320 --> 00:52:35,840 data points about these may have the that's not the right one. And they have the actual 417 00:52:35,840 --> 00:52:42,360 certificate here, I'd like to try to pull it up. If we can real quick. And so here's 418 00:52:42,360 --> 00:52:51,200 just a random one, we'll see if this is a full coa. See, this one's just a patient coa. 419 00:52:51,200 --> 00:53:01,280 So as I said, I've observed a mix of them in Florida. Ideally, we would like to get 420 00:53:01,280 --> 00:53:15,060 the official compliance coa, the compliance test for this cake face. Because that way 421 00:53:15,060 --> 00:53:21,920 we could know all the pesticides and everything in it. But okay, that's okay. Once again, 422 00:53:21,920 --> 00:53:30,560 as I said, we'll, this is an observation. So we can at least observe this data. So okay, 423 00:53:30,560 --> 00:53:43,840 so this is a cake face, flower, various levels of cannabinoids, you know, 28% total THC, 424 00:53:43,840 --> 00:53:51,640 almost 3% terpenes. So this is probably a flower that you would smell when you open 425 00:53:51,640 --> 00:54:02,960 the jar. I would assume. So so anywho, you know, lots of cool data points. Here, as I 426 00:54:02,960 --> 00:54:11,480 said, you know, we're missing a bunch of the pesticides and things. But in some of the 427 00:54:11,480 --> 00:54:17,560 terpenes, but this is a work in progress. So I'm going to share this data with you right 428 00:54:17,560 --> 00:54:25,800 after the meetup. And I'd encourage you all to look through it because you know, this 429 00:54:25,800 --> 00:54:29,920 is basically the cursory look I've been able to do. I've only really been able to basically 430 00:54:29,920 --> 00:54:36,040 just I mean, you you've already seen all the stuff I figured out, I basically figured out 431 00:54:36,040 --> 00:54:43,480 that, okay, some are compliance tests, and some are patient COAs. So that's as far as 432 00:54:43,480 --> 00:54:50,800 I've gotten. So that's what's, what's interesting about this is, although these are public, 433 00:54:50,800 --> 00:54:56,640 there's only so much time in the day. So, so maybe they're the ACS laboratories, and 434 00:54:56,640 --> 00:55:01,320 truly maybe they're scared to death about these lab results being out there. But it's 435 00:55:01,320 --> 00:55:08,000 like, you're maybe scared for no reason, because it's like, I haven't even had time to barely 436 00:55:08,000 --> 00:55:16,400 look at these. So once again, I encourage you all to take a look because like I said, 437 00:55:16,400 --> 00:55:25,960 there's no need to, I guess, in fact, I even kind of applaud truly even ACS labs for just, 438 00:55:25,960 --> 00:55:30,840 just getting these out there. Like I said, right, they're doing a lot of things running 439 00:55:30,840 --> 00:55:38,640 the H running the I don't even know what this instrument is the LC UV. But you know, they're, 440 00:55:38,640 --> 00:55:47,520 they're running these, you know, the ICPMS that's I want to say those may cost north 441 00:55:47,520 --> 00:55:56,000 of 200,000 or $300,000. And you probably need a specialized chemist to operate it. Right. 442 00:55:56,000 --> 00:56:01,660 So so that's what they're doing. They're running these scientific experiments. So or tests, 443 00:56:01,660 --> 00:56:08,560 so they only have so much time in their day. True leave is growing the actual cannabis. 444 00:56:08,560 --> 00:56:14,720 So they only have so much time in their day. So okay, you know, this is what they can do, 445 00:56:14,720 --> 00:56:25,040 they can post it online. Awesome. Then we can run the final mile. As Robert is finding 446 00:56:25,040 --> 00:56:33,760 out sometimes it's a bit more than a mile. But we can run this last little distance, 447 00:56:33,760 --> 00:56:39,360 you know, get the lab results. And now we can actually do something interesting with 448 00:56:39,360 --> 00:56:52,200 it. So someone was mentioning garlic. Well, we know about the beta pionene to D limonene 449 00:56:52,200 --> 00:56:59,680 ratio. And so this is just the first thing that I look at when I'm trying to understand 450 00:56:59,680 --> 00:57:06,080 a variety. I'm sure there's a lot more to this. So I encourage you all to look at these 451 00:57:06,080 --> 00:57:13,600 garlic strains. But it's like, okay, I look at the beta pionene to D limonene ratio, but 452 00:57:13,600 --> 00:57:26,080 it looks like they're kind of clustering around here, maybe 0.05 to 0.5. Okay, 0.05 to 0.5, 453 00:57:26,080 --> 00:57:39,480 about 0.1. Or this line, maybe 0.15 to 1.5, 0.15 to 1.5, once again, close to about 0.1. 454 00:57:39,480 --> 00:57:51,160 So about a 1 to 10 beta pionene to D limonene ratio. So right off the bat, my Bayesian hypothesis 455 00:57:51,160 --> 00:58:02,240 is this is a super strong indica, or what people would think of as an indica. So I kind 456 00:58:02,240 --> 00:58:08,920 of had a sneaking suspicion that may be the case. But now we actually have not many, but 457 00:58:08,920 --> 00:58:19,000 we've got 12 observations. So before, well, we maybe had some in different states. But 458 00:58:19,000 --> 00:58:29,240 in Florida, we had before this 0. Now we at least have 12 observations. And once again, 459 00:58:29,240 --> 00:58:35,680 these are rosins. So you'll have to look at the sample types and things like that. But 460 00:58:35,680 --> 00:58:43,240 already, I've never seen a ratio that low. Remember, I was telling you that I thought 461 00:58:43,240 --> 00:58:54,080 maybe the strongest indica was around 0.15. So now, this is now, I think, the strongest 462 00:58:54,080 --> 00:59:03,480 indica that I have personally observed. So now, that could maybe be an insight. Once 463 00:59:03,480 --> 00:59:09,080 again, take it with a grain of salt. And I encourage you all to do your own analysis. 464 00:59:09,080 --> 00:59:14,720 But now I kind of know. So it's like, okay, now when somebody says they've got garlic 465 00:59:14,720 --> 00:59:21,520 cake or garlic pop or garlic butter, before, I had no idea if that was more on the sativa 466 00:59:21,520 --> 00:59:27,240 side or indica side. Now I'm kind of thinking, okay, maybe it's more on the indica side. 467 00:59:27,240 --> 00:59:34,840 This one may put you to sleep. So once again, it may not. There's tons of more data exploration 468 00:59:34,840 --> 00:59:45,760 to do. But this is just a way that we can start making some rhyme or reason out of this. 469 00:59:45,760 --> 00:59:56,960 So once again, maybe various patients in Florida can augment this data. So maybe they're using 470 00:59:56,960 --> 01:00:04,560 all these samples. And then for each sample, maybe they're journaling, okay, you know, 471 01:00:04,560 --> 01:00:08,360 I had a good effect with this one. I had a bad effect with this one. I had a good effect 472 01:00:08,360 --> 01:00:16,280 with that one. Right? And then the patients could do their own personalized statistics. 473 01:00:16,280 --> 01:00:24,800 Because remember, 12, you only need eight observations to, once again, I may be butchering 474 01:00:24,800 --> 01:00:33,840 this, but from my understanding, if you can predict all eight of eight perfectly, then 475 01:00:33,840 --> 01:00:41,800 I think you can be 95% confident. I may be butchering those statistics. But, you know, 476 01:00:41,800 --> 01:00:46,080 if you were just reading these, you know, zero to one, you know, I like it or I don't 477 01:00:46,080 --> 01:00:52,040 like it. And you could then build a model that perfectly predicts that if you like it 478 01:00:52,040 --> 01:00:58,440 or you don't like it. And you can do it with a sample size of eight. I mean, you can do 479 01:00:58,440 --> 01:01:06,000 that, right? Maybe. Once again, it's always good to get your sample size large. And we're 480 01:01:06,000 --> 01:01:15,080 going to be working on that. But you can do a lot with a small sample. So I'll save some 481 01:01:15,080 --> 01:01:22,120 of this this cool AI material for you for next week, because there's no way I'll be 482 01:01:22,120 --> 01:01:28,600 able to, to get through it all today. And it's, it's, it's too much cool, good material 483 01:01:28,600 --> 01:01:35,120 to rush through. I know I spent forever just talking about COAs and data this time. So 484 01:01:35,120 --> 01:01:41,640 maybe not the funnest time ever. Hopefully found it interesting. Any thoughts, comments, 485 01:01:41,640 --> 01:01:48,720 I'll at least share the data set with you for coming in the code. 486 01:01:48,720 --> 01:02:00,320 It's kind of strange that they would have two different types of COAs available, that 487 01:02:00,320 --> 01:02:05,920 they would even split the market that way by not giving everyone all the information. 488 01:02:05,920 --> 01:02:13,120 Well, patients in Florida have to request compliance reports. I haven't found that online. 489 01:02:13,120 --> 01:02:19,120 But I found the compliance report on the like Facebook group for the medical patients. And 490 01:02:19,120 --> 01:02:25,000 you know, there's a lot. Yeah, there's a lot of data there. The patients are, you know, 491 01:02:25,000 --> 01:02:28,800 kind of getting smart too. Plus, you know, people are wondering, are their pesticides 492 01:02:28,800 --> 01:02:34,480 causing my stomach pain? Are the pesticides causing my lymph node issues? Right? I get 493 01:02:34,480 --> 01:02:40,440 it because there's some state weed that really makes my lymph nodes react and it never happens 494 01:02:40,440 --> 01:02:47,320 with my homegrown that's legal in Massachusetts. So, you know, as a patient, we really need 495 01:02:47,320 --> 01:02:51,860 to know about this, what's going on, how, you know, because there's a lot of rushing 496 01:02:51,860 --> 01:02:57,180 and corner cutting, you know, with the state weed, Florida has a real problem, you know, 497 01:02:57,180 --> 01:03:02,120 people open it up and it's moldy. And it's just, you know, there are people that like 498 01:03:02,120 --> 01:03:07,400 keep saying, maybe we should stick with legacy, it might be healthier. But I don't do legacy, 499 01:03:07,400 --> 01:03:15,800 you know, in Florida. So I have a card. Well, the glass, the bong half full on this one 500 01:03:15,800 --> 01:03:22,520 is the squeaky wheel gets the oil. And it's just like, you just have to keep trying. And 501 01:03:22,520 --> 01:03:27,920 I think I applaud all the patients in Florida, right? They've been squeaky. So they've, 502 01:03:27,920 --> 01:03:33,000 right, first they were squeaky, squeaky, squeaky, they got medical cannabis. And they're awesome. 503 01:03:33,000 --> 01:03:37,200 Well, they'll let's be squeaky, squeaky, squeaky, we want to know what's in our medical cannabis. 504 01:03:37,200 --> 01:03:45,520 And like, it's kind of like pulling teeth, you know, it's slowly, but in the night, to 505 01:03:45,520 --> 01:03:51,680 get to Hector's point, you know, oh, it's surprising that, you know, they're, you know, 506 01:03:51,680 --> 01:03:58,360 trying to withhold some of the lab results. And, you know, to me, it's not super surprising. 507 01:03:58,360 --> 01:04:09,200 And kind of like the, the Massachusetts public discussion, where, you know, even the, maybe 508 01:04:09,200 --> 01:04:14,320 the laboratories who are doing things correctly, they're just a little bit scared of people 509 01:04:14,320 --> 01:04:21,560 actually looking at the data. And so, you know, the labs aren't thrilled about the idea 510 01:04:21,560 --> 01:04:28,920 of their data being out there. The producers aren't super thrilled about having their screening 511 01:04:28,920 --> 01:04:34,960 tests out there. But as Candice pointed out, you know, it should be something that the 512 01:04:34,960 --> 01:04:40,200 consumers can at least see, right? They may not all look into it in depth, you know, they 513 01:04:40,200 --> 01:04:47,160 may not all be parsing COAs and applying statistics to them like we are, but you should at least 514 01:04:47,160 --> 01:04:54,840 be able to, you know, scan, or at least put your eyeballs over the COA. And this is where 515 01:04:54,840 --> 01:05:00,840 we get back to just keep being squeaky and keep asking, because unfortunately, it may 516 01:05:00,840 --> 01:05:06,480 come down to the kind of like in Washington, where there's actually just a state rule that 517 01:05:06,480 --> 01:05:13,560 says yes, if a consumer asks for a COA, you do have to show it to them. So I think that 518 01:05:13,560 --> 01:05:21,620 may not be a law in Florida. So it just may be people are asking for them. The producers 519 01:05:21,620 --> 01:05:28,720 realize there's that pressure there, and they're trying to, trying to pass that one off. But 520 01:05:28,720 --> 01:05:32,680 we're smart, right? And that's where we get back to at the beginning, right? The public 521 01:05:32,680 --> 01:05:38,720 smart. And so it's, you know, we, we figure that one out. It was like, it took me a second 522 01:05:38,720 --> 01:05:46,120 to, it was sort of a nice try. You know, it's like, thank you, you know, we do appreciate 523 01:05:46,120 --> 01:05:52,800 the the cannabinoids and terpenes. But ultimately, I think, you know, the rate, it's up to the 524 01:05:52,800 --> 01:05:57,960 patients in Florida, you know, if they want this, keep asking for it. But that's the thing 525 01:05:57,960 --> 01:06:03,360 is, make sure to ask for the, we want to see the compliance test. 526 01:06:03,360 --> 01:06:11,600 And that way, we could pick maybe a pesticide that we're not as allergic to, because you 527 01:06:11,600 --> 01:06:18,120 have to remember, patients, patients are where all this cannabis legalization were rooted 528 01:06:18,120 --> 01:06:24,000 from. And, and we just need to know, we need to know the additives put in, you know, the 529 01:06:24,000 --> 01:06:32,360 unnatural anything other than cannabis, is it in the weeds? Let us know. I don't know. 530 01:06:32,360 --> 01:06:40,760 I agree. I agree with you. And as I said, it's just, it's a sticky issue, sticky subject. 531 01:06:40,760 --> 01:06:48,320 And the only thing I know to do is just keep asking, keep collecting data, keep using statistics. 532 01:06:48,320 --> 01:06:59,800 It's a slow, slow process. But if anything, I think the the meeting in Massachusetts was 533 01:06:59,800 --> 01:07:06,200 sort of, you know, it's quite reassuring that we're on the right track. We're at least adding 534 01:07:06,200 --> 01:07:15,440 our voices to the conversation. And, you know, helping people learn and find out more and 535 01:07:15,440 --> 01:07:30,720 encouraging people to ask questions. So well, too cold. The lesson of the day today may 536 01:07:30,720 --> 01:07:38,680 be, make sure to read the fine print. Or especially read the fine print. That's where a lot of 537 01:07:38,680 --> 01:07:46,240 the interesting details are hiding. Well, thank you for staying extra long today. Thank 538 01:07:46,240 --> 01:07:52,840 you for coming, lending your eyes, your ears, your thoughts, questions, and keeping the 539 01:07:52,840 --> 01:08:00,040 conversation going. Thank you. Thanks, Keegan. Bye, everybody. See you next week. See you 540 01:08:00,040 --> 01:08:13,400 next week. Be productive.