MétaCan
Menu
Back to cohort
Record W4401504531 · doi:10.2139/ssrn.4917389

Broth Microdilution Protocol for Determining Antimicrobial Susceptibility of Legionella Pneumophila to Clinically Relevant Antibiotics

2024· preprint· en· W4401504531 on OpenAlexaff
Max Sewell, Caitlin Farley, Edward Portal, Diane Lindsay, Maria Luisa Ricci, Sophie Jarraud, Maria Scaturro, Ghislaine Descours, Anne Vatland Krøvel, Rachael Barton, Ian Boostom, Roisin Ure, Darja Keše, Valeria Gaia, Matej Golob, Susanne Paukner, Christophe Ginévra, Baharak Afshar, Sendurann Nadarajah, Ingrid Wybo, Charlotte Michel, Fedoua Echahdi, Juana Maria Gonzalez Rubio, Fernando González‐Camacho, M. Mentasti, Anastasia Flountzi, Markus Petzold, Jacob Moran‐Gilad, Søren Anker Uldum, Jonas M. Winchell, Mandy Wooton, Kathryn Bernard, Lucy C. Jones, Victoria J. Chalker, O. Brad Spiller

Bibliographic record

VenueSSRN Electronic Journal · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsBroth microdilutionLegionella pneumophilaMicrobiologyAntimicrobialAntibioticsLegionellaMedicineBiologyBacteriaMinimum inhibitory concentrationGenetics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0120.010

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 head0.025
GPT teacher head0.355
Teacher spread0.330 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations2
Published2024
Admission routes1
Has abstractno

Explore more

Same venueSSRN Electronic JournalSame topicLegionella and Acanthamoeba researchFrench-language works237,207