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Record W2129311586 · doi:10.1155/2007/563895

Who Provides Gastrointestinal Endoscopy in Canada?

2007· review· en· W2129311586 on OpenAlexafffundvenueabout
Robert J. Hilsden, Joshua Tepper, Paul Moayyedi, Linda Rabeneck

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2007
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoMcMaster University Medical CentreEmployment and Social Development CanadaUniversity of Calgary
FundersCanadian Association of Gastroenterology
KeywordsMedicineEndoscopyColonoscopySigmoidoscopyPrimary careFamily medicineGeneral surgeryRural areaSurgeryColorectal cancerInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

PURPOSE: To determine who provides gastrointestinal endoscopy in Canada and to understand provincial and regional differences in endoscopy providers. METHODS: Aggregate physician sociodemographic and activity data for 2002 were obtained from the Canadian Institute of Health Information's National Physician Database. Physicians were classified as gastroenterologists, general surgeons and others. RESULTS: In 2002, 1444 physicians, including 735 surgeons, 551 gastroenterologists and 158 others, performed at least 100 colonoscopies or 100 gastroscopies. Gastroenterologists performed 53% of all colonoscopies and 59% of all gastroscopies. Gastroenterologists were the primary providers of colonoscopies in large urban areas, whereas surgeons were the primary providers in smaller urban and rural areas. An average of 317 colonoscopies were performed by surgeons, 516 by gastroenterologists and 203 by other physicians. The proportion of surgeon colonoscopists in each province ranged from 47% to 71%. CONCLUSIONS: Surgeons and gastroenterologists are the major providers of gastrointestinal endoscopy in Canada, but the distribution of these providers among provinces and urban and rural areas varies. Although surgeon endoscopists are more numerous, on average, they perform fewer procedures annually than internists.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.294
Teacher spread0.258 · 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.

Study designNot applicable
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

Citations42
Published2007
Admission routes4
Has abstractyes

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