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Record W62035522 · doi:10.24095/hpcdp.29.1.02

Colorectal cancer screening in Canada: results of a national survey

2008· article· en· W62035522 on OpenAlexafffundvenueabout
Maida Sewitch, Caroline Fournier, Antonio Ciampi, Alina Dyachenko

Bibliographic record

VenueChronic diseases in Canada · 2008
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsMcGill UniversityRoyal Victoria HospitalSt Mary's Hospital CentreMcGill University Health Centre
FundersNational Cancer InstituteCanadian Institutes of Health ResearchMcGill University Health CentreMcGill University
KeywordsMedicineFecal occult bloodColorectal cancer screeningColorectal cancerCancer screeningColonoscopyNational Health Interview SurveyFamily medicineGerontologyDemographyCancerEnvironmental healthInternal medicinePopulation

Abstract

fetched live from OpenAlex

Canadian guidelines recommend colorectal-cancer (CRC) screening for individuals aged 50 to 74 years. The study objective was to estimate rates of CRC screening according to individual and geographical characteristics, and of adherence to current CRC screening guidelines. Respondents to the 2003 Canadian Community Health Survey Cycle 2.1 (aged >or= 50 years, without past or present CRC) participated. Fecal occult blood test (FOBT) and endoscopy utilization and screening rates were calculated. The sample included 16,747 residents of Newfoundland, Ontario, Saskatchewan and British Columbia. Overall, the FOBT screening rate was 7.7% in the past year, and the endoscopy screening rate was 8.8% in the past 5 years. FOBT screening rates were higher in older and male respondents; endoscopy screening rates were higher in older respondents. Individuals aged 50 to 59 and over 90 years were least likely to have been screened. Approximately 70% of respondents were non-adherent to current CRC screening guidelines. Non-adherence rates were higher in most health regions of British Columbia. National survey data suggest CRC screening in Canada is low; younger persons and residents of British Columbia were least likely to report CRC screening.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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

Citations32
Published2008
Admission routes4
Has abstractyes

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