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Record W2007849333 · doi:10.1097/aog.0b013e3181996ffa

Five-Year Experience of Human Papillomavirus DNA and Papanicolaou Test Cotesting

2009· article· en· W2007849333 on OpenAlexaff
Philip E. Castle, Barbara Fetterman, Nancy Poitras, Thomas Lorey, Ruth Shaber, Walter Kinney

Bibliographic record

VenueObstetrics and Gynecology · 2009
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsWomen's Health Research Institute
FundersNational Institutes of Health
KeywordsMedicinePapanicolaou stainPapanicolaou TestHuman papillomavirusGynecologyCervical cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: To estimate the 5-year age group-specific test positives for Pap tests and human papillomavirus (HPV) testing in a large, general screening population of women 30 and older. METHODS: Using data from Kaiser Permanente Northern California, a large health maintenance organization that introduced cotesting in 2003, we evaluated the cotesting results overall and by 5-year age groups. Women (n=580,289) who opted for and underwent cotesting (n cotests=812,598) between January 2003 and April 2008 were included in the analysis. Pap tests interpreted as atypical squamous cells of undetermined significance (ASC-US) or more severe were considered to be positive. Women were tested for carcinogenic HPV using an assay approved by the U.S. Food and Drug Administration. Binomial exact 95% confidence intervals (CIs) were calculated. RESULTS: Overall, 6.27% (95% CI 6.21-6.32%) of cotests were carcinogenic HPV positive, and only 3.99% (95% CI 3.94-4.03%) cotests had normal cytology and were carcinogenic HPV positive. By comparison, 5.18% (95% CI 5.13-5.23%) of cotests had ASC-US or more severe cytology, and 2.87% (95% CI 2.84-2.91%) of cotests had ASC-US or more severe cytology and were carcinogenic HPV negative. CONCLUSION: In a general screening population, concerns about excessive HPV test positives among women aged 30 years and older are not borne out.

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 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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
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)0.0000.000

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 head0.031
GPT teacher head0.331
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations111
Published2009
Admission routes1
Has abstractyes

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