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CIPARS Farm Program: Surveillance of antimicrobial use and antimicrobial resistance in Canadian swine herds

2009· article· en· W241528853 on OpenAlexaffabout
D. Léger, Anne Deckert, Sheryl Gow, B.P. Avery, Danielle Daignault, Lucie Dutil, Richard J. Reid‐Smith, R. Irwin

Bibliographic record

VenueInternational Conference on the Epidemiology and Control of Biological, Chemical and Physical Hazards in Pigs and Pork · 2009
Typearticle
Languageen
FieldVeterinary
TopicVeterinary medicine and infectious diseases
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsAntimicrobialHerdAntibiotic resistanceVeterinary medicineMicrobiologyMedicineBiologyAntibiotics

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) reduces our ability to effectively treat bacterial infections in animals and humans and is an issue of increasing public concern. AMR has been associated with the misuse of antibiotics in the human population but there is also concern with antimicrobial use in agri-food production. In order to provide science based infonnation on antimicrobial use and resistance in the swine industry, it is essential to collect and analyze information at the farm level. The Public Health Agency of Canada and its federal and provincial partners have developed the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) to monitor AMR and antimicrobial use (AMU) in Canada.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.282
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.351
Teacher spread0.269 · 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 teacher head, 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

Citations0
Published2009
Admission routes2
Has abstractyes

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