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Record W1981508868 · doi:10.3747/co.20.1568

Impact of the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology Clinical Practice Guidelines for Egfr and Alk Testing in Lung Cancer in Canada

2013· article· en· W1981508868 on OpenAlexaffvenueabout
Diana N. Ionescu

Bibliographic record

VenueCurrent Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsBC Cancer Agency
FundersNational Comprehensive Cancer NetworkAstraZeneca
KeywordsLung cancerMedicinePathologyMolecular pathologyAssociation (psychology)Clinical PracticeFamily medicineOncologyPsychologyBiology

Abstract

fetched live from OpenAlex

This paper summarizes the practical impact of the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology lung cancer biomarkers guidelines on the lung cancer approach in Canada, providing possible practical solutions for other similar health care systems in which scientific reality needs to be constantly balanced against economic reality.

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)0.025
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.130
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0040.004
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.094
GPT teacher head0.535
Teacher spread0.441 · 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 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

Citations13
Published2013
Admission routes3
Has abstractyes

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