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Record W118712044 · doi:10.1155/2007/817810

Colonoscopy and Flexible Sigmoidoscopy Practice Patterns in Ontario: A Population-Based Study

2007· article· en· W118712044 on OpenAlexaffvenueabout
Susan Schultz, Chris Vinden, Linda Rabeneck

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2007
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreWestern UniversityInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsSigmoidoscopyColonoscopyMedicinePopulationBowel preparationGeneral surgeryQuarter (Canadian coin)Colorectal cancerFamily medicineInternal medicineEnvironmental healthCancerGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: To conduct a population-based study on the provision of large bowel endoscopic services in Ontario. METHODS: Data from the following databases were analyzed: the Ontario Health Insurance Plan, the Institute for Clinical Evaluative Sciences Physicians Database and Statistics Canada. The flexible sigmoidoscopy and colonoscopy rates per 10,000 persons (50 to 74 years of age) by region between April 1, 2001, and March 31, 2002, were calculated, as well as the numbers and types of physicians who performed each procedure. RESULTS: In 2001/2002, a total of 172,108 colonoscopies and 43,400 flexible sigmoidoscopies were performed in Ontario for all age groups. The colonoscopy rate was approximately five times that of flexible sigmoidoscopy; rates varied from 463.1 colonoscopies per 10,000 people in the north to 286.8 colonoscopies per 10,000 people in the east. Gastroenterologists in all regions tended to perform more procedures per physician, but because of the large number of general surgeons, the total number of procedures performed by each group was almost the same. CONCLUSION: Population-based rates of colonoscopies and flexible sigmoidoscopies are low in Ontario, as are the procedure volumes of approximately one-quarter of physicians.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.284
Teacher spread0.268 · 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

Citations23
Published2007
Admission routes3
Has abstractyes

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