{"id":"W2492095263","doi":"10.1016/j.jtho.2016.06.028","title":"The IASLC Lung Cancer Staging Project: Methodology and Validation Used in the Development of Proposals for Revision of the Stage Classification of NSCLC in the Forthcoming (Eighth) Edition of the TNM Classification of Lung Cancer","year":2016,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":254,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"National Cancer Institute","keywords":"Medicine; Lung cancer; Stage (stratigraphy); Lung cancer staging; Cancer; Classification scheme; Metastasis; Oncology; Radiology; Medical physics; Internal medicine; Machine learning; Mediastinoscopy; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005854324,0.0001221916,0.0005226102,0.0001550177,0.0000959762,0.000005702612,0.000305295,0.000116081,0.00000675314],"category_scores_gemma":[0.0005538242,0.00004351453,0.000134356,0.0003565399,0.0002298676,0.0001148036,0.00004342088,0.0001884976,1.41937e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006195255,"about_ca_system_score_gemma":0.001226654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001533918,"about_ca_topic_score_gemma":0.0009105424,"domain_scores_codex":[0.9965328,0.001378757,0.001335834,0.0001513201,0.0004466778,0.0001546425],"domain_scores_gemma":[0.9938177,0.00236876,0.002948974,0.0003199889,0.0005280855,0.0000164252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002477194,0.0007835218,0.5457164,0.001919136,0.0004333936,0.000001008008,0.02534869,0.00006173929,0.1388493,0.001628184,0.000632034,0.2821494],"study_design_scores_gemma":[0.002274093,0.0005701486,0.8041191,0.003639221,0.0007929085,0.00001223755,0.006506762,0.0006486591,0.179728,0.0003227312,0.001307621,0.00007847667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795481,0.001237359,0.002562346,0.01413401,0.0003203875,0.002120774,0.00003041051,0.000001272134,0.00004534233],"genre_scores_gemma":[0.9965448,0.001062279,0.002048132,0.00004806271,0.00008711101,0.0001760745,0.000002831581,0.00001045466,0.00002019918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2820709,"threshold_uncertainty_score":0.2176031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1276468097578438,"score_gpt":0.4954103306432486,"score_spread":0.3677635208854048,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}