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Record W4410338594 · doi:10.1038/s44259-025-00108-0

Reviewing the complexities of bacterial biocide susceptibility and in vitro biocide adaptation methodologies

2025· review· en· W4410338594 on OpenAlexafffund
Peter O’Reilly, Genevieve Loiselle, Ryan Darragh, Carmine J. Slipski, Denice C. Bay

Bibliographic record

Venuenpj Antimicrobials and Resistance · 2025
Typereview
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiocideMicrobiologyAdaptation (eye)BiologyChemistry

Abstract

fetched live from OpenAlex

Decreased bacterial susceptibility to biocides raises concerns due to their influences on antibiotic resistance. The lack of standardized breakpoints, established methods, and consistent terminology complicates this research. This review summarizes techniques for studying biocide resistance mechanisms, susceptibility testing, and in-vitro adaptation methods, highlighting their benefits and limitations. Here, the challenges in studying biocide susceptibility and the need for standardized approaches in biocide research are emphasized for commonly studied biocide classes.

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.

How this classification was reachedexpand

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.103
GPT teacher head0.350
Teacher spread0.247 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2025
Admission routes2
Has abstractyes

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