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Record W4221006613 · doi:10.1016/j.jtho.2022.02.008

The International Association for the Study of Lung Cancer Staging Project: Methods and Guiding Principles for the Development of the Ninth Edition TNM Classification

2022· article· en· W4221006613 on OpenAlexaff
Frank C. Detterbeck, Katherine K. Nishimura, Vanessa Cilento, Meredith Giuliani, Mirella Marino, Raymond U. Osarogiagbon, Ramón Rami–Porta, Valerie W. Rusch, Hisao Asamura

Bibliographic record

VenueJournal of Thoracic Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer Centre
FundersNational Cancer InstituteJohnson and JohnsonGenentechNational Institutes of HealthAstellas PharmaAssociation of Community Cancer CentersTaiho PharmaceuticalMemorial Sloan-Kettering Cancer CenterGilead SciencesBristol-Myers SquibbEli Lilly and CompanyAstraZenecaChugai PharmaceuticalHope FoundationAstellas Pharma USLUNGevity FoundationIntuitive SurgicalPfizerCovidienInternational Association for the Study of Lung CancerAmerican Cancer Society
KeywordsMedicineLung cancer stagingNinthRelevance (law)Lung cancerStage (stratigraphy)Medical physicsPathology

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 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)0.005
metaresearch head score (Gemma)0.001
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 score0.687
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.126
GPT teacher head0.525
Teacher spread0.399 · 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

Citations45
Published2022
Admission routes1
Has abstractno

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