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Record W3087352119 · doi:10.1016/j.csbj.2020.09.012

A health metadata-based management approach for comparative analysis of high-throughput genetic sequences for quantifying antimicrobial resistance reduction in Canadian hog barns

2020· article· en· W3087352119 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueComputational and Structural Biotechnology Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsEnvironment and Climate Change CanadaGenome PrairieUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsResistomeBiotechnologyContext (archaeology)LivestockAntibiotic resistancePig farmingMetadataProduction (economics)BiologyBusinessAntibioticsComputer scienceAnimal productionWorld Wide WebGeneticsEcology

Abstract

fetched live from OpenAlex

New Canadian regulations have required that all use of antibiotics in livestock animal production should be under veterinary prescription and oversight, while the prophylactic use and inclusion of these agents in animal feed as growth promoters are also banned. In response to this new rule, many Canadian animal producers have voluntarily implemented production practices aimed at producing animals effectively while avoiding the use of antibiotics. In the swine industry, one such program is the 'raised without antibiotics' (RWA) program. In this paper, we describe a comprehensive investigative methodology comparing the effect of the adoption of the RWA approach with non-RWA pig production operations where antibiotics may still be administered on animals as needed. Our experimental approach involves a multi-year longitudinal investigation of pig farming to determine the effects of antibiotic usage on the prevalence of antimicrobial resistance (AMR) and pathogen abundance in the context of the drug exposures recorded in the RWA versus non-RWA scenarios. Surveillance of AMR and pathogens was conducted using whole-genome sequencing (WGS) in conjunction with open source tools and data pipeline analyses, which inform on the resistome, virulome and bacterial diversity in animals and materials associated with the different types of barns. This information was combined and correlated with drug usage (types and amounts) over time, along with animal health metadata (stage of growth, reason for drug use, among others). The overarching goal was to develop a set of interconnected informatic tools and data management procedures wherein specific queries could be made and customized, to reveal statistically valid cause/effect relationships. Results demonstrating possible correlations between RWA and AMR would support the Canadian pig industry, as well as regulatory agencies in new efforts, focused on reducing overall antibiotics use and in curbing the development and spread of AMR related to animal agriculture.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.060
GPT teacher head0.324
Teacher spread0.265 · 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