Bibliographic record
Abstract
This past contribution from our series BLOSSOMING TREASURES OF BIODIVERSITY [Biodiversity 5(4) 2004] has been chosen for presentation in this special issue on Food & Agriculture because it illustrates several important aspects of new crop development. First, it demonstrates the importance of crop research: in this case, millions of people forced by famine to consume a nutritious but toxic food can be spared agonizing paralysis by research aimed at developing new cultivated varieties with low levels of paralytic neurotoxin. Second, it shows that the benefits from crop research are usually not limited to the original target audience: in this case, not only has agriculture in subtropical countries benefitted by the creation of new cultivars useful for humans, but temperate region agriculture has also received new cultivars suitable as forage and fodder for livestock. Third, the cultural difficulties involved in implementing the benefits of non-toxic cultivars reminds us that the popularization of new crops often requires consideration of not only scientific and economic aspects, but also social constraints.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".