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Record W2774306832 · doi:10.12927/hcpol.2017.25322

A Review and Comparative Analysis of Information Targeted to the General Public on the Websites of Breast Screening Programs in Canada

2017· review· en· W2774306832 on OpenAlexaffvenueabout
Anne J. Kearney, Julie Polisena, Andra Morrison

Bibliographic record

VenueHealthcare policy · 2017
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsCanadian Agency for Drugs and Technologies in HealthMemorial University of Newfoundland
Fundersnot available
KeywordsMammographyMammography screeningBreast cancerMedicineBreast cancer screeningFamily medicineCancerInternal medicine

Abstract

fetched live from OpenAlex

Organized breast screening programs in Canada recommend that women, usually 50-74 years of age, are screened regularly with mammography to reduce their risk of breast cancer death. There is increasing evidence that estimates of mortality reduction are overestimated and harms under-reported. This article will report on a review of the websites of 12 breast screening programs in Canada. The primary goal is to determine what information is provided to enable women to make an informed decision about mammography and whether choice is emphasized. All publicly available English language information was extracted from the 12 websites by two independent reviewers, using a data extraction sheet. Information extracted included eligible age, screening interval and potential benefits and harms. This review is relevant to policy makers and breast screening program staff so they can determine what additional or alternative information is required on their websites to enable women to make informed decisions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
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 head0.424
GPT teacher head0.478
Teacher spread0.054 · 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 designOther design
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

Citations6
Published2017
Admission routes3
Has abstractyes

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