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Record W2063861058 · doi:10.3747/co.20.1566

Hereditary Colorectal Cancer Registries in Canada: Report from the Colorectal Cancer Association of Canada Consensus Meeting; Montreal, Quebec; October 28, 2011

2013· article· en· W2063861058 on OpenAlexafffundvenueabout
Heidi Rothenmund, Harminder Singh, Bernard Candas, B.N. Chodirker, Kim Serfas, Melyssa Aronson, Sabine M. Hölter, Alexandra Volenik, J. Green, Elizabeth Dicks, Michael O. Woods, Dawna Gilchrist, Robert Gryfe, Z. Cohen, William D. Foulkes

Bibliographic record

VenueCurrent Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill UniversityMemorial University of NewfoundlandUniversity of AlbertaUniversité LavalInstitut National de Santé Publique du QuébecUniversity of ManitobaMount Sinai HospitalHealth Sciences CentreCancerCare ManitobaJewish General Hospital
FundersCanadian Cancer Society Research InstituteJewish General HospitalConquer Cancer Foundation
KeywordsMedicineColorectal cancerFamily medicineHereditary CancerMultidisciplinary approachConsensus conferencePresentation (obstetrics)Lynch syndromeCancer geneticsCancerInternal medicineSurgery

Abstract

fetched live from OpenAlex

At a consensus meeting held in Montreal, October 28, 2011, a multidisciplinary group of Canadian experts in the fields of genetics, gastroenterology, surgery, oncology, pathology, and health care services participated in presentation and discussion sessions for the purpose of developing consensus statements pertaining to the development and maintenance of hereditary colorectal cancer registries in Canada. Five statements were approved by all participants.

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)0.023
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.010
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.301
Teacher spread0.271 · 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 designNot applicable
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
Published2013
Admission routes4
Has abstractyes

Explore more

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