Rob McCorkle, Co-Founder and COO of Emerald Metrics
Rob McCorkle is a Co-Founder and COO of Emerald Metrics. He also owns and operates a 10,000 sq ft indoor grow operation in Portland Oregon, KGB Farms. His experience in Spectral Imaging and his knowledge of Cannabis has allowed Emerald Metrics to transition quickly from working in large agriculture to now dominating the Cannabis market.
[00:00:01] You're listening to Thinking Outside the Bud where we speak with entrepreneurs investors thought leaders researchers advocates and policymakers who are finding new and exciting ways for cannabis to positively impact business society and culture. And now here is your host Business Coach Bruce Eckfeldt.
[00:00:30] Welcome everyone this is Thinking Outside The Bud. I'm Bruce Eckfeldt. I'm your host and our guest today is Robert McCorkle. And Robert is co-founder and CEO of Emerald metrics. And we're going to learn a little bit more about what they do and some fascinating technology. Fascinating history. So I'm excited by this interview. Rob welcome to the program. Thanks Bruce I appreciate it. Yeah. So let's start with the background. I'm always kind of curious how people sort of get into this space.
[00:00:53] You know I know you've got some background from a technology point of view and kind of our special point of view. So let's let's kind of cover that and then we can get into what Emerald metrics does and how you're using this technology in the cannabis space.
[00:01:05] Absolutely. So actually the other co-found one of the other co-founders and myself Chris rushing is another co-founder. He came at this from the military side and actually came to the technology through law enforcement side. I'm a retired lieutenant commander from a large police department. And we actually use spectral photography years ago throughout the years to look for certain signatures when really looking for you know large methamphetamine operations you know looking doing body searches in the desert or things like that. So we use spectral imaging.
[00:01:34] So actually let's let's just ground people. So when we're talking about spectral imaging what are we talking about here what is this technology.
[00:01:41] So what it is spectral imaging has been around since the 80s it was actually designed to develop like DARPA for NASA. So what spectral imaging is as we use hyper and multi spectral cameras to detect and codify the spectral code for any biologic we're looking at. So what a spectral barcode is how a certain biologic refract emits resource light at whatever level through the light spectrum that it is doing so and so from 0 to 700 nanometres every biologic in the world refraction emits and absorbs light at a different level. So we we detect that and then we write algorithms based around that so that our cameras can detect it anytime they see that in the future.
[00:02:20] Got it. So basically you're using cameras to basically develop a signal that that that's based on various wavelengths and things and then using the algorithm you can kind of turn that signal into a pattern or you can look for a pattern to say oh well this is this particular biologic or you know entity thing thing that is there whether it's you know very small scale or very large scale. That's the basis that the technology that I get that right.
[00:02:43] We make we like to call it a fingerprint spectral fingerprint. I like it because they're all unique. So we've spent years I just had Chris Christie met a military criminal law enforcement. But after that we developed a program for large agriculture. Well we were going to do about 20 acres a year using cameras that were mounted on the bottom of session of planes flying over 10000 acres at a time. And we would write the spectral code the algorithms what we were looking for in corn wheat and soy whether that's you know health anomalies nutrients in the ground pesticide drift whatever it might be. We would write the algorithms and then give that data back to the corn wheat soy farmer so that they make decisions on how where and when they're going to grow you know what kind of crops they're going to plant if they're not going to plan if they're going to take the crop insurance that year we give them that data. So we develop that program over about seven years and we handed it off to the parent company. Got it you know years we've been shrinking the cameras down getting better at writing algorithms for different types of biologics and now shrunk our cameras down to where they're about the size of a love an iPhone X is a good example about the size market and how I guess how details can you get.
[00:03:52] So if you're running a camera on the bottom of a Cessna or looking at a crop what's your what's your resolution or how could you describe that the detail that you can look at.
[00:04:01] Yes. So we can from 10000 feet up in the air we can get down to two centimeters on the ground two centimeters on the ground. OK. So I think probably it says Yeah. Think about it is we could pick out a single stock of corn in the middle of a 10000 acre field that had know wilt disease on it until the farmer exactly where to go to pull that one stock with corn so that the disease wouldn't spread to its corn crop.
[00:04:23] Wow. So you can you can get that level of kind of diagnostic or identification so that you get you can go down to single plants or single single entity is at that level.
[00:04:33] Ok. So for example indoors now our cameras we are actually down at the pixel level. If we find powdery mildew in one pixel of an image we can identify the grower.
[00:04:43] So and so the application obviously sort of logistics are a scenarios quite different right. You're going from you know plains looking at fields to I mean tens twenties of feet you know over you know over indoor crops. I mean what's the I guess what have been some of the challenges as you've kind of repurpose the technology into this new kind of market.
[00:05:05] The challenges have been field of view and being able to be within a price footprint that makes it to where it's a usable technology for indoor farmers. You know when we were running cameras on the bottom our systems our cameras were I think our cheapest camera time was five thousand dollars million. Now we've shrunk the cameras down to our cameras are down around the fifteen hundred two thousand dollars mark which is a. Huge difference. The same technology. So when we cut we build our own cameras we build our own technology. So we made it so our field of view our closest camera can go down to 30 inches away from the top of flower. And we get a field of view to be able to picture health and anomalies of the cannabis. So we have definitively developed camera systems that are far better than what we used to have for a much lower price point.
[00:05:56] Yeah. So there's there's a slight irony and the whole story you know two guys coming out of law enforcement and military now in cannabis coming out of us give us a sense of the. How did that come up how do you guys get into cannabis. Like what. What has been the journey like.
[00:06:11] So I actually got into cannabis right when I retired into law enforcement. My mother was diagnosed with brain cancer so I ended up taking some growers that I knew to grow medically up in Oregon because I wanted to make sure my mom was getting what she needed I didn't want her last year to be you know stuck on opioids. So I staked them they you know we built a very successful medical grow operation in Oregon that enabled my mom. In my opinion is the reason she lived for five more years rather than two more year. And then in 2016 we turned over me built to grow into a full full blown tier to 10000 square foot indoor grow rec operation in Oregon side of my building here in Oregon. In Portland Oregon about that same time Chris and I connected I'd use spectral imaging you know in law enforcement. He was actually a specter imaging officer in the military for years the Air Force. And we ended up realizing that our technology that I had used and he was developing was a natural fit for anomaly detection and cannabis. So I I pulled him kicking and screaming into the candidates. You know you came out of government you didn't understand the value proposition and you know he's a little worried about his top secret clearance. So I convinced him to let go with top secret clearance and become a cannabis guy.
[00:07:25] Yeah. And how was that transition going. I mean I think there's. I've spoken to a lot of people that have come out of either industries or professions or even just kind of cultural family religious situations that they you know there is there is kind of a shakedown. I mean there's a you know some of their friends some of their family kind of understand and accept that other ones don't. I mean I have. However you. I mean it sounds like you on the personal side had no family experience with your mother which you know sort of helped the transition. But as you work with other folks in the law enforcement and military how does that play out.
[00:07:55] It's interesting because one interesting characteristic of our technology is it's heavily used in government services but not heavily used in the private sector in a lot of ways hyper spectral is the more they use it. So a lot of the people that we are hiring are actually government people. So we have X military we're pretty heavy and we're military on we're pretty heavy you know hiring out of the military because that's where the expertise is. So our challenge has been so much with our family and such it's been the people that we've known for 20 30 years convincing them to come over and work on a project that's involved is something that for their whole career they've been told is illegal. So the conversations are interesting to say the least. But when they see you know what Chris and I are doing and the fact that we're you know we're legitimate all our business licenses we're a well except that our technology is is workable our technology is something that benefits the industry greatly and something nobody else has brought to the industry. We've found that willing to make that transition a lot easier than it would have been you know two or three years ago.
[00:08:57] Yeah there's it's the time some of this is just kind of timing and where the things are right.
[00:09:00] You know this is some of the you know the theater of operations is starting to cool off overseas and you know a lot of our friends are starting to come back to the US. You know they are looking for opportunities that don't require them to be over in the sands and different countries. So they're willing that they're willing to take a risk with us and it's been good.
[00:09:18] Yeah I'm sure. And that's a fascinating kind of re re application and kind of retraining or taking experience and capabilities from our armed forces and bring them down to private sector.
[00:09:28] So when you think about it I mean like coming out of military law enforcement you spend your career you know kind of on the other side not necessarily doing what you know is good and what the contrast you do. But in this industry we're actually doing something that benefits people benefits other entrepreneurs benefits society as a whole. So it's it's kind of us a second career field but we're still helping people that people actually like us and said hating our guts.
[00:09:51] That's nice. That's a nice fringe benefit to this end of this business.
[00:09:54] I still wake up and have people say hi and said Thank you.
[00:09:56] Yes exactly. It's shooting at you and stuff. So you kind of have these two business models and I'm kind of curious how how you kind of manage them so when I need you've got to grow a fairly big cultivation facility and operations and then you have this sort of technology company.
[00:10:10] I mean how I'm assuming you use your technology and your facility but how do you kind of balance the you know developing my cultivation capabilities versus taking all this technology and giving it to all their cultivators.
[00:10:21] Yes. So we're actually lucky that the emerald metrics company is actually located within our grow too. So everything we do on the metric side is tested on. Candidates all the time. So anything before we put anything out the door. We actually prove it with our own our and d rooms here in the Grove facility. So it's it kind of helps because I'm able to provide this technology to my own growers who've never had this opportunity before and we've used it to start developing strong analytics started codifying recipes you know things that have been in my growers brains for you know 20 30 years. We're now starting to say OK does that really work or does it work. And so any time they say hey I'd like to try this we set up tests here we and we prove definitively using technology and using the imaging systems whether it does or does not work because a lot of things in in cannabis that people think work people been doing 20 30 years and are convinced that that's the way to do it but nobody's ever really taken the time to actually prove that it works. And so that's what I'm doing in my own group and that is what we're doing is some of our other death row operations too. We're actually starting to prove previous thought or disprove the previous thought on how cannabis is or is not grown and what does and does not work. So I have found that in my growers have done great benefit from that because they've been able to let go of some longstanding ideas that they have in ways they had to grow and they've actually been able to streamline a lot of their processes by not doing things that they used to do or adding in pieces that they were afraid to add you know in the past because they didn't want to impact their you know it's almost like it's like the ultimate feedback device.
[00:11:57] It's okay you can run the experience the experiment and it's immediate.
[00:12:00] I mean you can with our system you can change nutrients and we can tell you within hours if the plant is is responding positively or negatively instead of waiting for you know the end when you look at your yield and your THC seem to be levels Turpin scales and all that we're going to tell you immediately whether the plant is responding on a positive vein or a negative b because it changes spectroscopy.
[00:12:21] So I get the the idea of like you know parasites and mold and surface level things you know.
[00:12:28] But I guess you know what. What can you see like how far into the plant can you see and what can you actually collect at all. I mean as a kind of digging into genetics and stuff like that can you look at whether strains are performing in certain ways. I mean what's the what's the limit.
[00:12:41] So were without getting you know too many beans we can we can do strain analytics we can tell different strains of cannabis purely through imaging because every strain has a different spectral code. We can have different anomalies I can tell you the between powdery mildew downy mole Brown Texas fungus we're in the process right now of trying to see if we can determine Tobacco Mosaic Virus there's nine viruses three of them may transition over to him none of transition of cannabis. So we're starting to log those so that when they do we can keep track of them. Now we could look at one of the biggest providers data providers we give to our growers is the health of their plants. Many of our growers no matter what we tell them want to go lay eyes on the plant and we tell them that something is not going right. And so I can tell them that you know hey it looks like you have nutrient toxicity in plant 12 rows six but I can't honestly tell them for sure whether it's nitrogen calcium magnesium whatever it may be on it. They have to go take a look that we can tell that it's manifesting is as a health issue and a nutrient issue. But because each strain manifests nutrients differently until we learn each specific strain which we will do when we're everybody. So now we can't be as specific as what the nutrient toxicity or deficiency is in the beginning as time goes on we'll be able to sample so I mean basically any more sample any more data more samples to be able to then do the algorithm against well to give an example just just to write the algorithm for powder build that we have to take 10000 images of powdery mildew. And that was only and powdery mildew you know manifest itself with a certain spectral code but we also want to find what that code looks like on every single strain of cannabis out there so that we miss it but that takes time.
[00:14:17] Ten thousand images to because we use the amazon eye. So you know it has to learn what that looks like. So that's what we do every day is teach our computers teach our servers what those images are based upon the spectral code that we collect.
[00:14:32] Got it interesting.
[00:14:34] So you get it so it sounds like not only can you you can decipher a lot right now but you can actually like that that will continually increase as you get more data and you have more cases and that's where the growers benefit from us being as many roads as possible is we maintain what's called an end user or library of all structural codes so the growers don't have access to everybody's information but they benefit from everybody's information so you know say you've got a grower that you know developed you know Lucy Brown Texas fungus you know not recombinant cannabis but we've actually found that up here in Oregon you may never see that and you may never ask us to find that anomaly for you but if we happen to find it in your grow. We already have that written and the computer is going to find it. We're not just going to find the stuff that we have found growing in your operation you're going to have access to what we found in everybody else's operation without ever really even knowing. It's just that end user library is there for everybody's use.
[00:15:27] Yeah I mean it's at some point you almost become. You know like an industry advocate or an industry resource of being able to identify like if you start to see you know a certain pathogen or something coming in and you know Southern California or something and you know it starts to work its way up. I mean you can identify some of these general industry risk stuff.
[00:15:45] Yeah. As we as we deploy to more and more grow up creations we'll be able to identify what we call it anomalies spread. Yeah. As things get brought into certain locations and people start buying clones or seeds or you know team plants from other locations and we see things starting to spread. We were able to do that in corn wheat and soy. We could we could backtrack to where we first started it and help figure out where it might have come from.
[00:16:07] Patient Zero. You can kind of hold on for that.
[00:16:10] That's a huge benefit to not only for the people who buy it but maybe the people who are sending out the samples don't even know they have it. Exactly. Talking about some of these systemic issues they don't manifest in clothes they don't even manifest in teams. They may not pop out until the plants start flowering. You know like TMI visas that don't manifest until you have flowering leaves that start. You know you see the modelling on the leaves. So if we can start tracking that back we can potentially track where it started from.
[00:16:36] Yeah. So tell me a little bit about the business model and how you how you interface with clients and stuff. So are you service based Are you Are you kind of are people paying upfront for the technology or are they just paying for the imaging itself. Like how have you decided to kind of model this from a business and deploy this for your customers.
[00:16:54] So our technology is sold as a hot hardware platform. We are not but that's not our revenue model. Our revenue model is SaaS software as a service. It's a monthly subscription fee based upon canopy coverage that is then broken down to an annual fee divided by twelve to be right. You know that's how we do it. So our hardware we've worked hard over the last few years getting the hardware costs down to a manageable level. And you know our cameras now are anywhere between like say they're right around fifteen hundred dollars a camera but then we put it. We put our camera we used to have to put our cameras on fixed location to the side grows. So we might have to put 10 or 20 cameras inside that grow operation now we're able to we've been able to move our cameras and take the pictures we need to God. I need to because they don't have to be stationary. We've changed our software and hardware to be able to do that. So now we're like in a 50 thousand square foot greenhouse where we might have had to put 10 cameras oftentimes I can put only two or three and they say that roving roving cameras on tracks and stuff. So that what we do is having those cameras back and forth we map out the facility we grid it out and we tell them you know the location that the cameras are starting to see anomalies spread and then the grower can make their decision.
[00:18:03] We call the three C's. They can either contain it cure it or kill it but we give them the information they need rather than sitting out scouts of as an example we've got a grower down in California who right now employs 20 scouts in its hundred fifty thousand square foot greenhouse operation. Once we're fully implemented that 20 person team will be cut down to five and all they're gonna do is respond to anomaly reports that they'll receive on their dashboard from us. So now they're not they're just responding looking into their containing curing or culling one of the biggest vectors of disease in plants in cannabis today is the human body. And we take things we don't see we're not using a proper leaning protocols Well using our system we won't be doing that anymore. You take the plant that we told you to go take a look at you take a three sided poster board you contain that plant and then you get into that plant to figure out what the issue is. You know we've probably told you what the issue is but you're going to confirm it and then you make your decision.
[00:18:55] So you're really doing the kind of data collection initial diagnostics and then letting people actually do the intervention you know with with an enhanced kind of understanding and dataset.
[00:19:04] Exactly. You know you know every every grower has their own their own IP strategy they've got their own their own way they like to deal with powdery mildew some natural curves so some just cool it. So we don't tell them how to fix it. We just tell them what to look for and where to look for it so they can fix it before it becomes a huge problem. We can see you know we can see things before the human eye can see them you know which you know when you're in your flowering stage is a big deal because if you're waiting a week for something to manifest onto the plant didn't in order to fix it you're waiting another week or two for the actual fix to take effect. Now we're seeing health issues within three to four hours of that actually manifesting onto the plant you know and giving you know a lot more lead time that you have a human eye.
[00:19:45] Yeah that makes sense when you you know as you've been developing the business. I'm curious where some of the challenges have been.
[00:19:51] You mentioned the hardware and getting the hardware down from big and expensive to small less expensive portable.
[00:19:58] What have been some of the other challenges you've kind of taken this technology and built this business around it understanding the technology understanding what the value prop is making sure that as the industry grows and is as there becomes less and less resources for people to go to to find out if they're doing the right thing growing in the right way. Technology is the way it's going to have to be. I mean that's just that's just the way as cannabis becomes a commodity. You're going to have to leverage technology to grow more with less in either the same or less amount of times in the same or less square footage. So our technology. Allows for labor savings and all those pieces but we have to explain that to them. A lot of people have their own systems and processes in place so we have to kind of convince them to interject our system into systems and processes that they might have been doing for 10 or 15 years already. So it's incumbent upon us to prove that value proposition. I'll give an example. We have a we have a clone table setup. You can run your clones underneath you take a tray clones put it underneath the clone the clone camera take a picture and 15 seconds later we'll tell you which of your clones are viable and which ones you should throw away. You know it takes such little energy to keep a clone a human eye and that we clones all the time that are not truly viable. Our software we can have we can set the parameters 70 80 90 100 percent of a whole spectrum. And then you could pick which clones you're going to move forward in my operation using my cloning camera last year it increased my yield by twelve point seven percent. I'm not going to get into numbers but to say that it was significant would be an understatement.
[00:21:26] Well tough fight. I mean whatever the numbers are it's going to that goes directly to the bottom line. Assuming you're just all the other all the other numbers are the same.
[00:21:34] Everything else remains the same. So when you look at what our clone camera alone can do on the return on investment it's in most of the groves that were in the clone camera pays not only for the rest of the facility implementation the SAS fee and everything plus profit. So just using the clone camera load is a no brainer.
[00:21:53] Yeah makes sense. Now you mentioned earlier just as the as this kind of market matures and there's kind of more price pressure on the cultivation side I mean is that when you look at the strategy of your business and kind of playing out the next couple years. Does that does that kind of commoditization or price pressure for cultivation. Is that kind of fuel is your expectation that's going to fuel use of your technology and technologies like it.
[00:22:18] Absolutely. We're already seeing that and even our pricing model you know our our mission our mission or from the very beginning is we want to be the very last thing that a grower lets go of as prices come down rather than the first piece of technology they jettison. We want to be the one piece that they can't do without. And that's why they develop it the way that we've developed it when it's fully implemented and people get used to using it and see the data and see that they are all either getting from it it's going to be a point that they can't get rid of it even when profits come down because it's the one thing that's going to keep their margins up. Yeah exactly.
[00:22:51] Yeah it certainly seems like that as far as the dynamics of this market shift that's going to be much more around companies that can grow profitably consistently at scale you know are gonna win the cultivation game that's suddenly gone.
[00:23:02] Yeah exactly when you when you look at when you look at where the industry is going as it becomes more mainstream has people become you know more used to which strains they like it's going to be incumbent upon the growers and the producers the producers to provide product that is consistent in quality and quantity so that the market is well it is you know as well sir the way you do that is by kind of find you strange recipes your systems your processes so that it's done the same every single time.
[00:23:30] And as in any commodity without without technology that's really hard to do one day to day basis based upon humans you know humans are fallible. You know we we have good days and bad days. Computers don't have good days and bad days. They may have days where they're off line and you get them back alive they're online and they're doing the exact same thing they did yesterday but they're not going to miss things that the human eye is going to miss.
[00:23:49] I'm curious just that maybe making a connection that's not there but you've been able to leverage this technology from your background in law enforcement and military other other things that you've found that you've been able to leverage there in terms of you know work ethic work ethic or approach or systems thinking or like what else have you found that has served you well as being you know people that have coming out of you know these these domains these industries you know what else have you been a plot be able to apply to this business.
[00:24:16] Well I'll make it simple for you know for 20 plus years I was called everything but a white man as a police officer even I. So I don't take insults out and I don't take no for an answer. I'm very good at explaining things. And so as Chris putting it across in a way that people can understand the value proposition pretty easily. So looking at what we're doing in the way we're doing it we both also come out of government so we understand that the price point has got to be something that people can manage and people can understand coming out of technology we all know that oftentimes technology is extremely expensive. And there's a lot of pushback. So we made the decision early on to make this something that was truly affordable not only for the growers and everything else but you know for the investors you have investors putting millions of dollars into these operations. I have no way of knowing whether they have no checks and balances. They've got no way of knowing if they're growers are doing the right thing or the wrong thing.
[00:25:08] So when we really looked at this we looked at it as like we want to provide something that not only benefits the growers but also benefits the people that are giving them the money to build the operations that they're building. So our dashboard is accessible to the investors. They can take a look at it however they want to set it up or the owners or the growers whoever they want to have access to it. We want. People to have information and that's that's kind of the quarter where businesses buy into the decision makers and the growers so they can grow and provide the best quality product to the market. Chris Chris and I work in military law enforcement worst used the long hours we're used to travel and read the you know meeting with people and convincing different things. So I think our our previous career paths. Well I'm an oddity in this industry is set us up to deal in something too in a way that other technology companies may not be able to to do.
[00:26:01] Yeah no I think that's very true. Have you noticed in terms of customers you've worked with you know attributes or things that tend to tend to make a customer a good customer or someone who can really use this technology to their advantage and strategically and those that just can. I mean what have you noticed in terms of good customers and also good customers.
[00:26:19] Well. So we actually turn down people who have asked us to use our system. And the reason we've done that is because unless they have true systems and processes in place to actually act upon the intelligence that we give them our system is pretty much work to ensure able and willing to see that you might have good or bad things going on in your grow and develop we tell you something that you can go in and fix it. The last thing I want is a grower with a reputation for you know putting moldy weed on the product to tell people that the aerial metric system. So we personally visit every single operation that we do a facility implementation in before they get it. We look at it we see what they're doing. We actually do our homework. We do our due diligence to make sure that they're ready actually ready to utilize our system. And if they're not we will work with them to develop those systems and processes we'll do scaled implementations maybe we'll just start about with a closed table to get them used to that system and process in there you know with the early cultivation help and wants to get to that and they see the value of true system and processes in APM strategies then we'll scale with them to do a full facility implementation. But if we don't think they're ready to use to actually use the technology and wanting to use it you know we either say no or we we propose some kind of a slow roll.
[00:27:35] Yeah that sounds like at some point you almost become a consultant for success before you start using technology.
[00:27:41] Let's make you're going to be it's kind of funny we actually we actually ended up doing that for some people and we're doing that for some real estate groups abstract built in and we imaged areas or locations that thinking about you know either building or buying a building we can image the building and telephone it has what we call artifacts and if it already has black mold in the facility we can tell them that if it's already got mold growing on the walls and no bug infestations in it then they can make you know purchase decisions based upon that data also. So yeah we do. We do act as a consultant for several groups now make sense.
[00:28:12] This has been fascinating really really educational we're gonna hit time here if people want to find out more about you about Emerald Metrics what's the best way to get that information that's right on our website is go to www.emeraldmetrics.com and all our contact information is on there all the information about the founders and the technology we're based in Portland Oregon.
[00:28:36] But you know we're doing operations in the states Canada, London, Paraguay a I wish I would have wanted. So we're kind of all over the map. So there's this trend that we won't take a look at the daily questions or you know they want to know about the technology. Feel free to call us. We're kind of an open book.
[00:28:54] Perfect. I'll make sure that the link is in the show notes here encourage people to go check it out.
[00:28:59] I've seen you guys a couple of shows it's really fascinating when you actually see the technology. I think it's you know it's definitely that's kind of next generation tech that is coming to play in cannabis so great stuff.
[00:29:09] Yeah. We're going to be at MJBiz Con of New Orleans, MJ biz Con of Vegas and Lift & coin Toronto. So those are the three next conventions that we're going to be at.
[00:29:17] Perfect. So I will I'll be at probably two out of three of those so I'll come I'll come say hi at those. Rob this has been great. Thank you so much for taking the time.
[00:29:25] All right. Sounds good. Thanks for your time.
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