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Record W2038762495 · doi:10.1016/s0960-9776(03)00100-0

Socioeconomic status & returning for a second screen in the Ontario breast screening program

2003· article· en· W2038762495 on OpenAlexaffabout
R.K Tatla, Lawrence Paszat, Susan J. Bondy, Z Chen, Anna M. Chiarelli, Verna Mai

Bibliographic record

VenueThe Breast · 2003
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreCancer Care Ontario
Fundersnot available
KeywordsMedicineRuralitySocioeconomic statusMammographyAttendanceBreast cancer screeningDemographyBreast cancerReferralRetrospective cohort studyCohortRural areaGerontologyFamily medicineEnvironmental healthCancerPopulationInternal medicine

Abstract

fetched live from OpenAlex

In a retrospective cohort study involving 57902 women initially screened between January 1, 1995 and December 31 1997 by the Ontario Breast Screening Program (OBSP), we examined the relationship between geographically derived socioeconomic status (SES) and returning for a second screen. We controlled for age, rurality, preferred language, initial mammography results, previous mammography history, and referral by a health professional. Although SES was related to returning, rurality was an effect modifier of this relationship, a finding not previously reported. Compared to women in the highest ('richest') quintile, urban women in the first and second quintile were less likely to return; this relationship was not found in rural women. Low SES women, particularly in urban areas, should be specifically targeted to increase their likelihood of re-attendance for breast cancer screening within an organized program.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.330
Teacher spread0.265 · 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 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

Citations39
Published2003
Admission routes2
Has abstractyes

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