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Record W2012787183 · doi:10.1071/sh11167

Epidemiology, natural history and risk factors for anal intraepithelial neoplasia

2012· review· en· W2012787183 on OpenAlexafffund
François Coutlée, Alexandra de Pokomandy, Eduardo L. Franco

Bibliographic record

VenueSexual Health · 2012
Typereview
Languageen
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsMcGill University Health CentreUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health Research
KeywordsAnal cancerMedicineNatural historyMen who have sex with menGonorrheaEpidemiologyHPV infectionGenital wartsImmunologyRisk factorCervical intraepithelial neoplasiaGynecologyInternal medicineCancerCervical cancerHuman immunodeficiency virus (HIV)Syphilis

Abstract

fetched live from OpenAlex

Studies conducted in HIV-seropositive individuals have enhanced our understanding of the natural history of anal intraepithelial neoplasia (AIN) and of factors predictive of progression to high-grade AIN, the immediate precursor to anal cancer. AIN is frequently detected in HIV-seropositive individuals. Factors that increase the risk for AIN include HIV infection, low current or nadir blood CD4+ cell counts, receptive anal intercourse, oncogenic human papillomavirus (HPV) infection, persistent anal HPV infection, multiple HPV type infections and high anal HPV viral load. This review confirms the importance of high-grade AIN in HIV-seropositive individuals and HIV-seronegative men having sex with men.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.176
GPT teacher head0.400
Teacher spread0.225 · 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

Citations25
Published2012
Admission routes2
Has abstractyes

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