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Record W2582429707

Estimated antimicrobial dispensing frequency and preferences for lactating cow therapy by Ontario dairy veterinarians.

2017· article· en· W2582429707 on OpenAlexaffabout
David Léger, Nathalie C. Newby, Richard J. Reid‐Smith, Neil G. Anderson, David L. Pearl, K. Lissemore, D.F. Kelton

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsMinistry of Agriculture, Food and Rural Affairs
Fundersnot available
KeywordsAntimicrobial stewardshipMedicineAntimicrobialFamily medicineVeterinary medicineAntibiotic resistanceBiologyAntibioticsMicrobiology
DOInot available

Abstract

fetched live from OpenAlex

In this cross-sectional study, data were collected from responses to a questionnaire on dispensing frequencies of antimicrobials used by dairy practitioners in Ontario in dairy cattle in 2001. Data were validated through clinical case scenarios. Respondents reported using antimicrobials across all categories of importance to human medicine (medically important, Categories I to III) with a diversity of treatment combinations and routes of administration. Respondents anticipated that a request for direct veterinary supervision by producers was dependent on case severity, highlighting the importance of on-farm diagnostic and treatment protocols. Knowledge of the antimicrobials used in lactating cow therapy, and their frequency and reasons for use, will provide baseline information and contribute to antimicrobial stewardship in this food-animal production sector.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.999

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.106
GPT teacher head0.266
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2017
Admission routes2
Has abstractyes

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