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Record W2902375374 · doi:10.3138/jammi.2018-0024

Canadian guidelines on HIV pre-exposure prophylaxis (PrEP) and non-occupational post-exposure prophylaxis (nPEP): Discussion beyond the guidelines and commentary on the role of infectious diseases specialists

2018· article· en· W2902375374 on OpenAlexaffvenueabout
Ameeta E. Singh, Darrell H. S. Tan, Mark Hull, Isaac I. Bogoch, Paul MacPherson, Cécile Tremblay, Stephen D. Shafran

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCentre Hospitalier de l’Université de MontréalOttawa HospitalUniversity of British ColumbiaToronto General HospitalSt. Michael's HospitalUniversity of Alberta
Fundersnot available
KeywordsPre-exposure prophylaxisGuidelineMedicineFamily medicinePost-exposure prophylaxisPsychological interventionHuman immunodeficiency virus (HIV)Alternative medicineMen who have sex with menEnvironmental healthPathologyNursing

Abstract

fetched live from OpenAlex

Pre-exposure prophylaxis (PrEP) and non-occupational post-exposure prophylaxis (nPEP) are part of combination HIV prevention strategies that include behavioural interventions such as condoms and risk-reduction counselling. A 25-member panel was convened to develop Canadian guidelines for PrEP and nPEP, with the full guidelines recently published in the Canadian Medical Association Journal (CMAJ). This article provides a discussion beyond the guideline, highlighting areas of particular interest to infectious disease (ID) specialists and discusses the possible role of ID specialists as access to both PrEP and nPEP become more widely available across the country.

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)0.034
metaresearch head score (Gemma)0.122
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.109
Threshold uncertainty score0.577

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.122
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.008
Science and technology studies0.0100.011
Scholarly communication0.0070.005
Open science0.0100.004
Research integrity0.0240.029
Insufficient payload (model declined to judge)0.0060.002

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 head0.007
GPT teacher head0.273
Teacher spread0.267 · 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
GenreCommentary

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

Citations3
Published2018
Admission routes3
Has abstractyes

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