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Record W2888957691 · doi:10.14745/ccdr.v40is2a05

Canadian integrated program for antimicrobial resistance surveillance: Retail food highlights, 2003–2012

2014· article· en· W2888957691 on OpenAlexaffvenueabout
B.P. Avery, E. Jane Parmley, RJ Reid-Smith, Danielle Daignault, RL Finley, R. Irwin

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsCampylobacterSalmonellaAntibiotic resistanceVeterinary medicineLivestockBiologyPopulationTetracyclineCiprofloxacinRaw meatFood scienceBacteriaMicrobiologyEnvironmental healthAntibioticsMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) is a collaborative, integrated program designed to track antimicrobial resistance (AMR) among enteric bacteria isolated from various livestock commodities along the food-producing continuum ("farm to fork") and in humans. OBJECTIVE: To provide a summary of the prevalence and trends in AMR among select bacteria isolated from raw, fresh chicken, pork, and beef in 2012 at the retail food level and to link these data with other findings from CIPARS. METHODS: was tested in beef and pork. Data were analyzed for 2012 and temporal and regional trends were examined between 2003 and 2012 by province/region. RESULTS: in retail beef remained low (≤1%) and was also relatively low comparable to previous years in pork. CONCLUSION: In Canada, as is the case worldwide, there is evidence of resistance to medically important antimicrobials among bacteria from retail meats. Resistance among organisms isolated from poultry, beef, and pork at the retail food level is characterized by wide variation over time and across different regions.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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 designNot applicable
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

Citations16
Published2014
Admission routes3
Has abstractyes

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