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Record W2067745694 · doi:10.1155/2012/503432

Performance of a New HPV Cervi-Collect Collection and Transportation Kit

2011· article· en· W2067745694 on OpenAlex
Max Chernesky, Shihai Huang, D. Jang, Brian Erickson, John Salituro, Herbert Engel, Jodi Gilchrist, Paul Michael Neuscheler, Wai-Bing Mak, Klara Abravaya

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Oncology · 2011
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineKappaHuman papillomavirusInternal medicine

Abstract

fetched live from OpenAlex

Background. Liquid-based Pap (L-Pap) media are used for Pap and human papillomavirus (HPV) testing. Objectives. To compare RealTime High Risk (HR) HPV testing of a new collection kit (Cervi-Collect) and PreservCyt L-Pap specimens. To determine ease of use and safety of Cervi-Collect. Methods. L-Pap samples (n = 203) were tested with HC2 and RealTime HR HPV and Cervi-Collect with RealTime HR HPV. Discordant samples were genotyped. Results. L-Pap and Cervi-Collect specimens tested by RealTime HR HPV showed 93.1% agreement (Kappa 0.86). RealTime HR HPV and HC2 on L-Pap had 90.3% agreement (Kappa 0.80). RealTime HR HPV on Cervi-Collect and HC2 on L-Pap showed 88.2% agreement (Kappa 0.76). Sixteen of 21 samples which were HC2 negative and RealTime HR HPV positive on L-Pap or Cervi-Collect contained HR HPV genotypes. Eleven healthcare collectors were in strong agreement on a usability and safety questionnaire. Conclusion. Cervi-Collect samples were easy to collect and showed strong agreement with L-Pap samples tested with RealTime HR HPV or HC2.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.078
GPT teacher head0.357
Teacher spread0.279 · 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