MétaCan
Menu
Back to cohort

Lessons from the Environmental Antibiotic Resistome

2017· review· en· W2600203898 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.

Bibliographic record

VenueAnnual Review of Microbiology · 2017
Typereview
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsResistomeAntibiotic resistanceResistance (ecology)AntibioticsBiologyEcosystemEcologyAquatic ecosystemDiversity (politics)MicrobiologyIntegronPolitical science

Abstract

fetched live from OpenAlex

Antibiotic resistance is a global public health issue of growing proportions. All antibiotics are susceptible to resistance. The evidence is now clear that the environment is the single largest source and reservoir of resistance. Soil, aquatic, atmospheric, animal-associated, and built ecosystems are home to microbes that harbor antibiotic resistance elements and the means to mobilize them. The diversity and abundance of resistance in the environment is consistent with the ancient origins of antibiotics and a variety of studies support a long natural history of associated resistance. The implications are clear: Understanding the evolution of resistance in the environment, its diversity, and mechanisms is essential to the management of our existing and future antibiotic resources.

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)0.001
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 score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.005

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 head0.073
GPT teacher head0.385
Teacher spread0.312 · 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