Bibliographic record
Abstract
La grande histoire de l’amelioration genetique bovine et des taureaux d’insemination artificielle de ces trente dernieres annees racontee et illustree par la petite histoire de quelques taureaux reproducteurs : les grandes evolutions technologiques dans les deux aspects techniques de la reproduction et de l’amelioration genetique seront expliquees. Le point d’orgue en sera la rupture technologique de l’avenement de la « genomique » a savoir le decryptage des genomes et la lecture de l’ADN ; les interactions entre nos cinq regions, Bretagne, Pays de la Loire, Normandie, Centre et Poitou, et le reste de la France et les pays majeurs de l’elevage bovin, Etats-Unis, Canada, Allemagne, Pays-Bas, Angleterre ou dans une moindre mesure la Belgique, la Colombie ou l’Irlande ; quelques-unes des principales races bovines francaises ; l’organisation generale de l’elevage en France, en allant de la recherche scientifique avec l’INRA et l’ITEB (puis Idele), a l’administration (Ministere et directions regionales), aux organismes d’eleveurs…
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".