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Record W2027207177 · doi:10.1186/1472-6874-4-s1-s13

Cancer of the Uterine Cervix

2004· article· en· W2027207177 on OpenAlexaffabout
Eliane Duarte‐Franco, Eduardo L. Franco

Bibliographic record

VenueBMC Women s Health · 2004
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineCervical cancerIncidence (geometry)CytologyTriageCancerGynecologyCervixObstetricsInternal medicinePathologyMedical emergency

Abstract

fetched live from OpenAlex

HEALTH ISSUE: Cervical cancer is one of the most common malignant diseases of women; it is diagnosed in almost half a million women every year and half as many die from it annually. In Canada and other industrialized countries, its incidence has decreased due to cytology screening. However, invasive cases still occur, particularly among immigrant groups and native Canadian women. Although incidence of squamous cell carcinomas has decreased, the proportion of adenocarcinomas has increased because Pap cytology is ineffective to detect these lesions. KEY FINDINGS: In Canada, cervical cancer will cause an estimated 11,000 person-years of life lost. In most Canadian provinces, early detection is dependent on opportunistic screening. Primary prevention can be achieved through health education (sexual behavior modification) and vaccination to prevent infection from Human Papillomavirus (HPV). The initial results from vaccination trials are encouraging but wide scale use is more than a decade away. DATA GAPS AND RECOMMENDATIONS: Most cases of cervical cancer occur because the Pap smear was either false negative, was not done or not done often enough. Appropriate recommendations and guidelines exist on implementation of cytology-based programs. However, most Canadian women do not have access to organized screening. Further research is needed to 1) evaluate automated cytology systems; 2) define appropriate management of precursor lesions and 3) deliver definitive evidence of HPV testing efficacy in long-term follow-up studies with invasive cancer as an outcome and 4) provide Canadian data to justify augmenting or modifying current programs to use HPV testing in secondary triage of equivocal Pap smears.

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)0.000
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 score0.541
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 head0.057
GPT teacher head0.419
Teacher spread0.362 · 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.

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

Citations50
Published2004
Admission routes2
Has abstractyes

Explore more

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