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Record W2539347450 · doi:10.1097/coh.0000000000000339

Clinical and scientific challenges in HIV-associated malignancies

2016· article· en· W2539347450 on OpenAlexaff
Mark N. Polizzotto, Ronald T. Mitsuyasu

Bibliographic record

VenueCurrent Opinion in HIV and AIDS · 2016
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer Institute
KeywordsBoulevardHuman immunodeficiency virus (HIV)Library scienceMedicineSuiteFamily medicineGeographyArchaeology

Abstract

fetched live from OpenAlex

aKirby Institute for Infection and Immunity, University of New South Wales bSt Vincent's Hospital Sydney, Sydney, Australia cClinical AIDS Research and Education (CARE) Center, University of California Los Angeles, Los Angeles, California, USA Correspondence to Dr Mark N. Polizzotto, Kirby Institute for Infection and Immunity, Wallace Wurth Building, UNSW Australia, Sydney 2052, Australia. Tel: +61 2 9385 0900; fax: +61 2 9385 0955; e-mail: [email protected]; Dr Ronald T. Mitsuyasu, CARE Center, University of California Los Angeles, 11075 Santa Monica Boulevard, Suite 100, Los Angeles, CA 90025, USA. Tel: +1 310 825 3807; fax: +1 310 477 7657; e-mail: [email protected]

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)0.026
metaresearch head score (Gemma)0.039
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: Review · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0080.011
Open science0.0020.005
Research integrity0.0080.015
Insufficient payload (model declined to judge)0.0100.004

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 head0.106
GPT teacher head0.366
Teacher spread0.260 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

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