MétaCan
Menu
Back to cohort
Record W2806228813 · doi:10.14745/ccdr.v42i04a04f

Recommandations provisoires concernant la déclaration des isolats ultrarésistants et panrésistants de la famille des Enterobacteriaceae, de Pseudomonas aeruginosa, du genre Acinetobacter spp. et de Stenotrophomonas maltophilia

2016· article· fr· W2806228813 on OpenAlexaffvenue
GJ German, FB Jamieson, Matthew W. Gilmour, Huda Almohri, James M. Bullard, MC Domingo, J Fuller, Gabriel Girouard, David Haldane, Lan Hoàng, P N Levett, Jean Longtin, Roberto G. Melano, Robert Needle, SN Patel, Anu Rebbapragada, RC Reyes, M. R. Mulvey

Bibliographic record

VenueRelevé des maladies transmissibles au Canada · 2016
Typearticle
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicInfections and bacterial resistance
Canadian institutionsSaskatchewan Disease Control LaboratoryInstitut National de Santé Publique du QuébecDr. Georges-L.-Dumont University Hospital CentreProvincial Laboratory of Public HealthPublic Health Agency of CanadaPublic Health OntarioBC Centre for Disease ControlQueen Elizabeth II Health Sciences CentreSt. John’s Health Sciences CentreHealth PEI
Fundersnot available
KeywordsStenotrophomonas maltophiliaStenotrophomonasMicrobiologyEnterobacteriaceaeAcinetobacterPseudomonas aeruginosaBiologyPseudomonasBacteriaEscherichia coliAntibioticsGene

Abstract

fetched live from OpenAlex

Les recommandations de cette publication doivent être considérées comme étant préliminaires pendant un an à partir de la date de publication.Les commentaires sur le document doivent être envoyés au D r Michael Mulvey.Tous les commentaires reçus seront examinés par le sous-comité sur la résistance aux antimicrobiens du Réseau des laboratoires de santé publique du Canada avant que les recommandations finales soient rédigées et publiées.

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)0.049
metaresearch head score (Gemma)0.102
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0040.004
Scholarly communication0.0060.003
Open science0.0040.003
Research integrity0.0180.013
Insufficient payload (model declined to judge)0.0070.005

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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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
GenreOther

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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueRelevé des maladies transmissibles au CanadaSame topicInfections and bacterial resistanceFrench-language works237,207