MétaCan
Menu
Back to cohort
Record W3134991961 · doi:10.1128/aem.00242-21

Local Adaptation of Legionella pneumophila within a Hospital Hot Water System Increases Tolerance to Copper

2021· article· en· W3134991961 on OpenAlexafffund
Émilie Bédard, Hana Trigui, Jeffrey Liang, Margot Doberva, Kiran Paranjape, Cindy Lalancette, Séverine Allegra, Sébastien P. Faucher, Michèle Prévost

Bibliographic record

VenueApplied and Environmental Microbiology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsSte. Anne's HospitalMcGill UniversityPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsLegionella pneumophilaLegionellaBiofilmMicrobiologyAdaptation (eye)CopperLegionnaires' diseaseBiologyBacteriaChemistry

Abstract

fetched live from OpenAlex

Legionella pneumophila is a pathogen indigenous to natural and large building water systems in the bulk and the biofilm phases. The immediate environment within a system can impact the tolerance of L. pneumophila to environmental stressors, including copper.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations25
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueApplied and Environmental MicrobiologySame topicLegionella and Acanthamoeba researchFrench-language works237,207