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Record W4392368785 · doi:10.1016/j.jtho.2024.02.011

The International Association for the Study of Lung Cancer Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groups in the Forthcoming (Ninth) Edition of the TNM Classification for Lung Cancer

2024· article· en· W4392368785 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Thoracic Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersSun Yat-sen University Cancer CenterBoehringer IngelheimCentro de Investigación Médica Aplicada, Universidad de NavarraUniversity of SydneyUniversity of Colorado Colorado SpringsNational Cancer InstituteArthrex GmbHAIO-StudienInstituto Nacional do Câncer, Ministério da SaúdeShanghai Chest HospitalPeking UniversityAstraZenecaInstitut National Du CancerAll-India Institute of Medical SciencesTechnische Universität MünchenShanghai Jiao Tong UniversityUniversity of QueenslandInstituto Nacional de CancerologíaSeoul National University Bundang HospitalColumbus State UniversityUniversité LavalInternational Association for the Study of Lung CancerMassachusetts General HospitalGuangdong Provincial People's HospitalIcahn School of Medicine at Mount Sinai
KeywordsMedicineNinthLung cancerStage (stratigraphy)Lung cancer stagingLungTNM staging systemOncologyInternal medicineCancerNeoplasm staging

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.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.481
Teacher spread0.440 · 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