Environmental Biofilms as Reservoirs for Antimicrobial Resistance
Bibliographic record
Abstract
Characterizing the response of microbial communities to a range of antibiotic concentrations is one of the strategies used to understand the impact of antibiotic resistance. Many studies have described the occurrence and prevalence of antibiotic resistance in microbial communities from reservoirs such as hospitals, sewage, and farm feedlots, where bacteria are often exposed to high and/or constant concentrations of antibiotics. Outside of these sources, antibiotics generally occur at lower, sub-minimum inhibitory concentrations (sub-MICs). The constant exposure to low concentrations of antibiotics may serve as a chemical "cue" that drives development of antibiotic resistance. Low concentrations of antibiotics have not yet been broadly described in reservoirs outside of the aforementioned environments, nor is the transfer and dissemination of antibiotic resistant bacteria and genes within natural microbial communities fully understood. This review will thus focus on low antibiotic-concentration environmental reservoirs and mechanisms that are important in the dissemination of antibiotic resistance to help identify key knowledge gaps concerning the environmental resistome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".