Research Magazine Summer 1999 - Focus: Plant Research
Bibliographic record
Abstract
In this issue:They'll be hungry when they arrive; Plant agriculture...qu'est-ce sue c'est?; Where it's at for plants; Getting tough on corn disease; Name that flavone; Wild beets to the rescue; A bean for all reasons; They're in canola's corner; Super selection; The $60-million difference; Surviving the big chill; Animal-saving plants; A bite for life; The business of plant agriculture; Biotechnology, Mega project is mindful of the environment; Deal with it; Closing in on nutrients; Pasture is profitable; Petal perfect; Ultra violets; A strawberry 350 years in the making; The green new world of cosmic crops; Plants that grow when the lights are low; Pigging out on barley; Superior vines, superior wines; Pressing for purity; A multi-million-dollar boost aMAIZEing stress tolerance; The comeback currant; Fresh from the tropics of Simcoe; Leaving a pesticide paper trail; Well-weathered transgenic plants; Curbing energy consumption; Which weed's which?; Internationally friendly; Communications focus on food risks; Winners in the wrap category; A challenge to the Georgia peach; Building a better apple orchard; An ancient remedy takes root in Ontario; The Mushroom Man vs. Green mould; Behind the bean scene; Time for soy; When breeding was the pits; Stretching the supply; Tough tomato transplants
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.360 | 0.363 |
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".