Approche Proposée pour Lâétablissement de Teneurs Maximales en Vitamines, en Minéraux Nutritifs et en Acides Aminés Dans les Boissons, les Préparations pour Boissons, les Concentrés de Boissons, les Poudres, les Barres et les Confiseries Admissibles à fai
Bibliographic record
Abstract
Faisant suite à un processus interne d’examen par les pairs mené par ses experts scientifiques et réglementaires, la Direction\ndes aliments de Santé Canada met ce document à la disposition du public afin de pouvoir prendre en compte les\ncommentaires des scientifiques, des régulateurs et des parties prenantes avant la finalisation du document.\nCe document est ouvert aux commentaires du 2 Juin 2014 jusqu’au 2 Août 2014 (60 jours calendaires). Seuls les\ncommentaires à caractère scientifique seront pris en compte dans l'élaboration de la version finale de ce document. Les\nauteurs s'efforceront de documenter la façon dont les différents commentaires ont été reçus, et lorsque ceux – ci auront été\njugé pertinents, ils seront pris en compte dans la version finale du document publié.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.021 |
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".