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Record W4392931790 · doi:10.1016/j.jtho.2024.03.015

The International Association for the Study of Lung Cancer (IASLC) Staging Project for Lung Cancer: Recommendation to Introduce Spread Through Air Spaces as a Histologic Descriptor in the Ninth Edition of the TNM Classification of Lung Cancer. Analysis of 4061 Pathologic Stage I NSCLC

2024· article· en· W4392931790 on OpenAlexafffund
William D. Travis, Megan Eisele, Katherine K. Nishimura, Rania G. Aly, Pietro Bertoglio, Teh‐Ying Chou, Frank C. Detterbeck, Jessica Donnington, Wentao Fang, Philippe Joubert, Kemp H. Kernstine, Young Tae Kim, Yolande Lievens, Hui Liu, Gustavo Lyons, Mari Mino–Kenudson, Andrew G. Nicholson, Mauro Papotti, Ramón Rami–Porta, Valerie W. Rusch, Shuji Sakai, Paula A. Ugalde, Paul Van Schil, Chi‐Fu Jeffrey Yang, Vanessa Cilento, Masaya Yotsukura, Hisao Asamura

Bibliographic record

VenueJournal of Thoracic Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersSun Yat-sen University Cancer CenterUniversity of SydneyUniversity of Colorado Colorado SpringsNational Cancer InstituteArthrex GmbHInstituto Nacional do Câncer, Ministério da SaúdeShanghai Chest HospitalPeking UniversityAll-India Institute of Medical SciencesTechnische Universität MünchenShanghai Jiao Tong UniversityUniversity of QueenslandInstituto Nacional de CancerologíaChartered Institute of Management AccountantsSeoul National University Bundang HospitalColumbus State UniversityUniversité LavalMassachusetts General HospitalInstitut National Du CancerMemorial Sloan-Kettering Cancer CenterInternational Association for the Study of Lung CancerGuangdong Provincial People's HospitalIcahn School of Medicine at Mount SinaiB.P. Koirala Institute of Health SciencesBoehringer Ingelheim
KeywordsMedicineLung cancerLymphovascular invasionAdenocarcinomaStage (stratigraphy)Univariate analysisCancerOncologyInternal medicineRadiologyPathologyMultivariate analysisMetastasis

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)0.008
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.053
GPT teacher head0.477
Teacher spread0.423 · 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

Citations85
Published2024
Admission routes2
Has abstractno

Explore more

Same venueJournal of Thoracic OncologySame topicLung Cancer Diagnosis and TreatmentFrench-language works237,207