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Record W3105880525 · doi:10.1002/vms3.390

Antibiotic use in pig farming and its associated factors in L County in Yunnan, China

2020· article· en· W3105880525 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVeterinary Medicine and Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersKunming Medical UniversityInternational Development Research Centre
KeywordsAntibioticsAgriculturePurchasingLivestockPig farmingChinaEnvironmental healthAgricultural scienceMedicineGeographyVeterinary medicineBiotechnologyBusinessAnimal productionBiologyAnimal scienceMarketing

Abstract

fetched live from OpenAlex

China has a long history of pig rearing, and it currently raises and consumes approximately half of the pigs in the world. Major improvements have been made in pig farming in China in the last four decades with the growing application of new livestock farming technologies. Among the new improvements, the use of antibiotics in pig farming is a common but not well-documented practise. In order to understand the behaviour of the farmers regarding antibiotic use in pig farming, we conducted a household survey in four townships of L County in Yunnan Province, China, during August 2014 and April 2015. In this survey, 404 farmer households were interviewed using a questionnaire. Among the farmers interviewed, 89% reported easy access to antibiotics, 83.7% reported experience of self-purchasing antibiotics, and 40.3% reported that they often used antibiotics in pig farming mainly for the prevention and treatment of pig diseases. These farmers identified 20 antibiotics that they had used in pig farming 6 months before the survey. Of these, 11 and 8 antibiotics have been categorised under 'critically important' and 'highly important' antimicrobial groups, respectively, by the World Health Organization (WHO), and 12 and 8 have been categorised under the 'Watch' and 'Access' groups, respectively, as per the 2019 WHO AWaRe classification of antibiotics. Factors associated with the behaviour of self-purchasing antibiotics included types of farms, sources of antibiotics, and previous experiences of pig diseases: those who were smallholders, buying antibiotics from veterinary drugstores and village vets, and whose pigs had suffered diseases previously were more likely to self-purchase antibiotics for their pigs. Farmers who cleaned their pigsties less frequently and those whose pigs had suffered from diseases used antibiotics more frequently as compared to their peer farmers.

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.

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)0.000
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 score0.285
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.108
GPT teacher head0.322
Teacher spread0.213 · 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