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Record W2588287780 · doi:10.3949/ccjm.84a.15049

Postexposure management of infectious diseases

2017· review· en· W2588287780 on OpenAlexaff
Mazen S. Bader, Annie Brooks, Deborah Kelly, Jocelyn A. Srigley

Bibliographic record

VenueCleveland Clinic Journal of Medicine · 2017
Typereview
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsUniversity of British ColumbiaMemorial University of NewfoundlandProvincial Health Services AuthorityOntario Clinical Oncology GroupJuravinski HospitalMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMedicineInfection controlIntensive care medicineInfectious disease (medical specialty)Transmission (telecommunications)Health careDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Anyone exposed to an infectious disease--whether a healthcare provider, patient, or contact of a patient--should be evaluated promptly and the source of the infection identified. A systematic response entails postexposure prophylactic therapy if available and indicated, infection control measures to prevent further transmission, counseling and educating those involved, and assessing those who may require work restriction or modification.

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)0.001
metaresearch head score (Gemma)0.004
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.185
GPT teacher head0.494
Teacher spread0.310 · 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
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

Citations5
Published2017
Admission routes1
Has abstractyes

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