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Record W2619881204 · doi:10.1093/cid/cix101

The Effect of Antibiotic Exposure and Specimen Volume on the Detection of Bacterial Pathogens in Children With Pneumonia

2017· article· en· W2619881204 on OpenAlexaff
Amanda J. Driscoll, Maria Deloria Knoll, Laura L. Hammitt, Henry C. Baggett, W. Abdullah Brooks, Daniel R. Feikin, Karen L. Kotloff, Orin S. Levine, Shabir A. Madhi, Katherine L. O’Brien, J. Anthony G. Scott, Donald M. Thea, Stephen R. C. Howie, Peter V. Adrian, Dilruba Ahmed, Andrea N. DeLuca, Bernard E. Ebruke, Caroline W. Gitahi, Melissa M. Higdon, Anek Kaewpan, Angela Karani, Ruth A. Karron, Razib Mazumder, Jessica McLellan, David P. Moore, Lawrence Mwananyanda, Daniel E. Park, Christine Prosperi, Julia Rhodes, Md. Khaled Saifullah, Phil Seidenberg, Samba O. Sow, Boubou Tamboura, Scott L. Zeger, David R. Murdoch

Bibliographic record

VenueClinical Infectious Diseases · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsUniversity of Calgary
FundersWellcome Trust
KeywordsAntibioticsMedicineSputumPneumoniaStreptococcus pneumoniaeMicrobiological cultureBlood culturePathogenMicrobiologySputum cultureInternal medicineBacteriaGastroenterologyImmunologyPathologyBiologyTuberculosis

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.004
metaresearch head score (Gemma)0.028
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.280
Teacher spread0.269 · 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

Citations96
Published2017
Admission routes1
Has abstractyes

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