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Record W2071714106 · doi:10.1111/zph.12192

The Establishment of the Colombian Integrated Program for Antimicrobial Resistance Surveillance (COIPARS): A Pilot Project on Poultry Farms, Slaughterhouses and Retail Market

2015· article· en· W2071714106 on OpenAlexaboutno aff
Pilar Donado-Godoy, Luis R. Castellanos, Maribel León, A. Arevalo, Viviana Clavijo, Johan Fabian Bernal, Dallas S Leon, Mc Allister Tafur, Barbara A. Byrne, William A. Smith

Bibliographic record

VenueZoonoses and Public Health · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsnot available
FundersInstituto Colombiano AgropecuarioCenters for Disease Control and PreventionInstituto Nacional de Salud
KeywordsPoultry farmingBusinessEpidemiological surveillanceRetail tradeVeterinary medicineMedicineCommerceEpidemiology

Abstract

fetched live from OpenAlex

The development of antimicrobial resistance among bacteria (AMR) is currently one of the world's most pressing public health problems. The use of antimicrobial agents in humans and animals has resulted in AMR which has narrowed the potential use of antibiotics for the treatment of infections in humans. To monitor AMR and to develop control measures, some countries, such as the USA, Canada and Denmark, have established national integrated surveillance systems (FDA, , CIPARS, 2007, DANMAP,2002). The components of these programs monitor changes in susceptibility/resistance to antimicrobial agents of selected zoonotic pathogens and commensal organisms recovered from animals, retail meats and humans. The rapid development of Colombia's animal production industry has raised food safety issues including the emergence of antibiotic resistance. The Colombian Integrated Surveillance Program for Antimicrobial Resistance (COIPARS) was established as a pilot project to monitor AMR on poultry farms, slaughter houses and retail markets.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.168
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.290
Teacher spread0.240 · 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

Citations68
Published2015
Admission routes1
Has abstractyes

Explore more

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