Comparison of GBR and HARVARD models in assessing bovine spongiform encephalipathy (BSE) risk using data up to 2003
Bibliographic record
Abstract
Deux modèles d évaluation de risque ESB majeurs, le modèle Harvard (MH) et le Geographical-BSE Risk (GBR) sont comparés en utilisant des données provenant de trois pays précédemment évalués par la Commission Européenne (Uruguay, Danemark et le Système Nord Américain constitué des Etats-Unis et du Canada). Cette étude démontre que le Modèle Harvard (HM) envisage exclusivement les conséquences de l importation d infectivité ESB au sein des pays, soit par l intermédiaire d animaux en incubation, soit par des farines animales infectées par l agent de l ESB. Au contraire, le GBR ne considère dans son fonctionnement que la possibilité qu a un pays d avoir importé le prion, à une période donnée, et ce uniquement d un abord strictement qualitatif. Il semble que, pour évaluer le risque effectif lié à l ESB, il faille associer à la fois les aspects quantitatifs et qualitatifs de ces deux modèles, leur utilisation séparée ne permettant que d aborder une des facettes limitée de l évaluation du risque.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".