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Record W2949741751 · doi:10.3390/microorganisms7060180

Antibiotic Pollution in the Environment: From Microbial Ecology to Public Policy

2019· review· en· W2949741751 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.

Bibliographic record

VenueMicroorganisms · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsConcordia University
Fundersnot available
KeywordsAntibiotic resistanceUnintended consequencesAntibioticsResistance (ecology)CornerstoneEnvironmental planningEcologyPollutionBiologyEnvironmental healthEnvironmental resource managementGeographyPolitical scienceMedicineEnvironmental scienceMicrobiology

Abstract

fetched live from OpenAlex

The ability to fight bacterial infections with antibiotics has been a longstanding cornerstone of modern medicine. However, wide-spread overuse and misuse of antibiotics has led to unintended consequences, which in turn require large-scale changes of policy for mitigation. In this review, we address two broad classes of corollaries of antibiotics overuse and misuse. Firstly, we discuss the spread of antibiotic resistance from hotspots of resistance evolution to the environment, with special concerns given to potential vectors of resistance transmission. Secondly, we outline the effects of antibiotic pollution independent of resistance evolution on natural microbial populations, as well as invertebrates and vertebrates. We close with an overview of current regional policies tasked with curbing the effects of antibiotics pollution and outline areas in which such policies are still under development.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.043

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 head0.046
GPT teacher head0.307
Teacher spread0.261 · 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