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Record W1971623971 · doi:10.1097/jto.0b013e3182a46c0c

CDKN2A/p16 Inactivation Mechanisms and Their Relationship to Smoke Exposure and Molecular Features in Non–Small-Cell Lung Cancer

2013· review· en· W1971623971 on OpenAlexaff
Kit Tam, Wei Zhang, Junichi Soh, Victor Stastny, Min Chen, Han Sun, Kelsie L. Thu, Jonathan J. Rios, Chenchen Yang, Crystal N. Marconett, Suhaida A. Selamat, Ite A. Laird‐Offringa, Ayumu Taguchi, Samir Hanash, David S. Shames, Xiaotu Ma, Michael Q. Zhang, Wan L. Lam, Adi F. Gazdar

Bibliographic record

VenueJournal of Thoracic Oncology · 2013
Typereview
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsBC Cancer Agency
FundersNational Institute of Environmental Health SciencesNational Institutes of HealthNational Cancer InstituteNational Human Genome Research InstituteUniversity of Texas Southwestern Medical CenterCanary Foundation
KeywordsCDKN2AKRASCancer researchMethylationDNA methylationPoint mutationLung cancerMutationCarcinogenesisBiologyGeneMedicineMolecular biologyGeneticsGene expressionOncology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.395
Teacher spread0.359 · 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
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

Citations108
Published2013
Admission routes1
Has abstractno

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