Microbial antibiotic resistance genes across an anthropogenic gradient in a Canadian High Arctic watershed
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.
Bibliographic record
Abstract
Abstract Antibiotic resistance is one of the biggest challenges to public health. While the discovery of antibiotics has decreased pathogen-caused mortality, the overuse of these drugs has resulted in the increased transfer and evolution of antibiotic resistance genes (ARGs) in bacteria. ARGs naturally occur in wild bacterial communities, but are also found in increased concentrations in environments contaminated by wastewater effluent. Although such ARGs are relatively well described in temperate environments, little is known about the distribution and dissemination of these genes in the Arctic. We characterized the ARGs in microbial communities from aerosols, lakes and microbial mats around a remote Arctic hamlet using metagenomic approaches. Specific objectives were to (i) compare ARGs across habitats, (ii) to characterize ARG populations along a continuum of anthropogenically influenced environments, and (iii) to identify ARGs of viral origin. We identified ARGs in all habitats throughout the watershed, and found that microbial mats in the most impacted area had the highest diversity of ARGs relative to uncontaminated sites, which may be a remnant signal of wastewater effluent inputs in the area during the 20th century. Although we identified ARGs predominantly in bacterial genomes, our data suggests that mimiviruses may also harbor ARGs.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it