MétaCan
Menu
Back to cohort
Record W756350558 · doi:10.1300/j077v19n03_03

Population Screening for Colorectal Cancer

2001· article· en· W756350558 on OpenAlexaffabout
Richard Schabas

Bibliographic record

VenueJournal of Psychosocial Oncology · 2001
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFecal occult bloodColorectal cancerMedicineContext (archaeology)Colorectal cancer screeningPopulationHealth careTest (biology)OccultFamily medicineGynecologyCancerEnvironmental healthColonoscopyInternal medicineAlternative medicinePolitical sciencePathologyGeography

Abstract

fetched live from OpenAlex

Screening with fecal occult blood testing (FOBT) and a follow-up bowel assessment is an evidence-based opportunity to reduce mortality from colorectal cancer. Health policy requires that population screening meets specified criteria, such as those identified by Wilson and Jungner for the World Health Organization. This article examines key criteria for FOBT screening in the context of the Canadian health care system, which places a high value on equitable access to services. Screening with FOBT is a suitable test that could be applied population-wide. Facilities for diagnosis and treatment are available provided a high-specificity FOBT is used. Finding real cost savings will be difficult, however. Canadian provinces are likely to opt to deliver colorectal screening through independently organized programs.

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)0.001
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: none
Teacher disagreement score0.914
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.048
GPT teacher head0.402
Teacher spread0.355 · 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

Citations6
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Psychosocial OncologySame topicColorectal Cancer Screening and DetectionFrench-language works237,207