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Record W2008501341 · doi:10.3747/co.v18i5.775

Canadian College of Medical Geneticists Guidelines for the Indications, Analysis, and Reporting of Cancer Specimens

2011· article· en· W2008501341 on OpenAlexaffvenueabout
Angelika J. Dawson, Jean McGowan‐Jordan, Judy Chernos, Jie Xu, Josée N. Lavoie, J.C. Wang, Michelle Steinraths, Susheel Shetty

Bibliographic record

VenueCurrent Oncology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsVictoria General HospitalHealth Sciences CentreMontreal Children's HospitalMcMaster UniversityLondon Health Sciences CentreAlberta Children's HospitalMcGill UniversityChildren's Hospital of Eastern OntarioShared Health
Fundersnot available
KeywordsMedicineFamily medicineCancer geneticsCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

The Canadian College of Medical Geneticists (ccmg) is a national organization of medical and laboratory geneticists. The mission of the ccmg is to establish and maintain high-quality professional and ethical standards for medical genetics services in Canada and to help to ensure that service of the highest quality is delivered to the Canadian public.Cancer cytogenetics is one of the sections of practice of the ccmg. The ccmg Cytogenetic Committee has, therefore, put forward guidelines to provide oncologists and ccmg cytogeneticists with a comprehensive review of the cytogenetic diagnostic tests that are recommended as a minimum standard of care for tumours of hematopoietic and lymphoid tissues and for tumours of soft tissue and bone. The guidelines were approved by the ccmg board of directors in June 2010.

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)0.017
metaresearch head score (Gemma)0.031
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: Methods · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0120.010
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0060.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0190.006

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 head0.211
GPT teacher head0.477
Teacher spread0.265 · 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
GenreMethods

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

Citations12
Published2011
Admission routes3
Has abstractyes

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