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Record W7099430961

PII S0360-3016(99)00327-2 CLINICAL INVESTIGATION Large Bowel A POPULATION-BASED STUDY OF RECTAL CANCER: PERMANENT COLOSTOMY AS AN OUTCOME

2014· article· en· W7099430961 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsColostomyColorectal cancerRadiation therapyLogistic regressionOdds ratioMultivariate analysisMedical recordRelative risk
DOInot available

Abstract

fetched live from OpenAlex

Purpose: The objectives of this study are to describe the utilization of surgery and of radiotherapy in the treatment of newly diagnosed rectal cancer in Ontario between 1982 and 1994, and to describe the probability of permanent colostomy at any time after the diagnosis of rectal cancer, as an outcome of the treatment of newly diagnosed rectal cancer. Methods and Materials: Electronic records of rectal cancer (International Classification of Diseases code 154) from the Ontario Cancer Registry (n 5 18,695, excluding squamous, basaloid, cloacogenic, and carcinoid histology) were linked to surgical records from all Ontario hospitals, and radiotherapy (RT) records from Ontario cancer centers. Procedures occurring within 4 months of diagnosis, or within 4 months of another procedure for rectal cancer, were considered part of initial treatment. Multivariate analyses controlled for age, sex, and year of diagnosis. Results: Resection plus permanent colostomy was performed in 33.1 % of cases, whereas local excision or resection without permanent colostomy was performed in 38.2%. Multivariate logistic regression demonstrated higher odds ratios (OR) for resection plus permanent colostomy in all regions of Ontario relative to Toronto. The OR for postoperative RT following local excision or resection without permanent colostomy varied among the regions relative to Toronto (e.g., OR Ottawa 5 0.59, OR Hamilton 5 0.76, OR London 5 1.25). The relative risk

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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