The CannaLock Pollination Bag: Creating the First Pollination Bag for Cannabis
Bibliographic record
Abstract
Cannabis sativa L., bred for psychoactive or non-psychoactive purposes, is a recently restored crop industry in Canada and the United States. While the attention of modern plant breeding programs has yielded new insights into Cannabis L. as a genus, the lack of economical and effective pollination tools hampered genetic gains. In 2018, no specific pollination bag was on the market that could manage pollen across the polymorphic species of Cannabis sativa L. while maintaining a productive growing environment. Cannabis breeders improvised their pollination management methods and tools, often mistaking the pollen size of their plants. The CannaLock Pollination Bag, the first pollination bag specifically designed for cannabis, was created to meet the needs of cannabis breeders. Creating the CannaLock Pollination Bag began by immersing myself in the cannabis industry and learning the crop’s taxonomy, life cycle, sex expression, pollination, and varying breeding goals. I familiarized myself with the makeshift methods cannabis breeders used to manage pollen. I held Discovery Meetings with cannabis breeders across the United States, building a reputation of trust, profiling their knowledge of pollen variability, identifying their wants, and proposing solutions through value selling. I then coordinated the creation of several prototypes and sold them firsthand to testers. I studied customer feedback across domestic and international breeders to determine the prototype with the highest success rate. Prototype success or failure, often a determinant of pore size, indirectly divulged the range of viable pollen sizes across plants ranging from approximately 21 to 30+ microns. The CannaLock Pollination Bag was the final product. The CannaLock Pollination Bag is now being used by premier cannabis breeders worldwide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".