Reprinted from: Perspectives on new crops and new uses. 1999.
Bibliographic record
Abstract
In the past three years, there has been a renewed interest in the production of fiber hemp (Cannabis sativa L., Cannabinaceae) in Alberta. This effort has sparked a great deal of interest and speculation regarding the crop’s potential. Since 1995 fiber hemp research plots have been grown in various parts of Alberta to evaluate the potential of this crop for both seed and fiber production (Blade 1998). Research licenses were granted by the Health Protection Branch of Health Canada, the branch of the federal government charged with enforcing legislation concerning this species. In March, 1998, Health Canada announced that commercial production of low-THC hemp would be allowed through a licensing process. Hemp is an annual herbaceous plant which flourishes in temperate regions (Bosca and Karus 1998). All cultivars tested in Alberta have been low-THC (delta-9-tetrahydrocannabinol) genotypes. Canada has adopted the 0.3 % THC standard established by the European Union and the OECD as the concentration which separates non-psychoactive strains suitable for legal fiber production from those which are illegally grown for their properties of intoxication. The 0.3 % THC designation is very
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.204 | 0.110 |
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".