{"id":"W4220659516","doi":"10.1016/j.jtho.2022.02.013","title":"NSCLC Subtyping in Conventional Cytology: Results of the International Association for the Study of Lung Cancer Cytology Working Group Survey to Determine Specific Cytomorphologic Criteria for Adenocarcinoma and Squamous Cell Carcinoma","year":2022,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"AI in cancer detection","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sunnybrook Health Science Centre; Health Sciences Centre; Université Laval; Princess Margaret Cancer Centre","funders":"Merck Sharp and Dohme; Daiichi-Sankyo; Takeda Pharmaceutical Company; AbbVie; Chugai Pharmaceutical; Roche; Novartis; GlaxoSmithKline; Amgen; Pfizer; Bayer; AstraZeneca; Eli Lilly and Company; University of Missouri; U.S. Department of Defense","keywords":"Subtyping; Adenocarcinoma; Cytology; Medicine; Lung cancer; Gold standard (test); Oncology; Carcinoma; Algorithm; Internal medicine; Cancer; Pathology; 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":[0.005203614,0.0001216701,0.0004395301,0.0003001885,0.00020435,0.00002501027,0.001091112,0.00009816005,0.00001140015],"category_scores_gemma":[0.0004814744,0.0000933492,0.0001154237,0.0004246878,0.00005910355,0.0001153084,0.0004846003,0.0003518121,6.471878e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210099,"about_ca_system_score_gemma":0.0002640124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002183605,"about_ca_topic_score_gemma":0.001654681,"domain_scores_codex":[0.9970822,0.001067993,0.0009638797,0.0002939992,0.0003565811,0.0002353367],"domain_scores_gemma":[0.9940594,0.003367007,0.001875006,0.0002328443,0.0004310396,0.00003466204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009869779,0.0008459213,0.9489403,0.00005999101,0.0001372706,0.00003533568,0.004318928,0.003094066,0.009147441,0.0001328157,0.003290888,0.02012722],"study_design_scores_gemma":[0.003755013,0.003829562,0.9739899,0.00002184375,0.00008419275,0.000206088,0.000847794,0.01385366,0.001528278,0.0002803241,0.001482641,0.0001207297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767247,0.000641036,0.01454625,0.002758979,0.004301469,0.0009293573,0.00007312193,0.000004549308,0.0000204905],"genre_scores_gemma":[0.9972971,0.00001292212,0.002129924,0.0001562915,0.0001921451,0.0001609381,0.000003078218,0.000009942825,0.00003765569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02504953,"threshold_uncertainty_score":0.380667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06734476077710362,"score_gpt":0.3816303051502155,"score_spread":0.3142855443731119,"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."}}