Data_Sheet_1_Assignment of Canadian Defined Daily Doses and Canadian Defined Course Doses for Quantification of Antimicrobial Usage in Cattle.docx
Bibliographic record
Abstract
<p>Standardized units are essential to allow quantification and comparison of antimicrobial usage (AMU) between species and regions. In Canada, defined daily and course doses have not yet been harmonized for cattle. Our objective was to assign defined daily and course doses (named DDDbovCA and DCDbovCA, respectively) for cattle in Canada, by antimicrobial agent (AM) and by route of administration, based on the label of all products containing at least one AM, marketed and authorized in Canada for use in cattle. In April and December 2019, a systematic search was performed from the online Drug Product Database (DPD) of Health Canada to identify veterinary products containing at least one AM, marketed in Canada for use in cattle. Products were divided by route of administration (intramammary, intrauterine, injectable, oral, and topical). The monograph was retrieved for each product from the DPD, or from the Canadian Edition of the Compendium of Veterinary Products (CVP), and read completely to extract recommended dosages in cattle. Standard weights were applied to compute doses if required. DDDbovCA and DCDbovCA were assigned by calculating an average of daily and course doses, respectively, by AM and route of administration. Two products were excluded from calculations because of their claim as growth promotion or feed efficiency (no longer authorized in Canada for certain categories of AM). Overall, 39 injectable, 75 oral (including 23 medicated premixes), 8 intramammary (4 for lactating cows and 4 for dry cows), 5 intrauterine, and 4 topical products were used for calculations. DDDbovCA and DCDbovCA values were assigned successfully for each AM identified, by route of administration. These metrics will allow harmonized and transparent quantification of AMU in cattle in Canada.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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 teacher head, 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".