{"id":"W4413607291","doi":"10.64628/aap.fywsn9p3n","title":"Lung cancer: Predicting which patients are at high risk of recurrence to improve outcomes","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Lung cancer; Cancer; Medicine; Oncology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008644546,0.0003891996,0.0005582213,0.0007847258,0.0002480439,0.001288389,0.0003627318,0.0007115608,0.01301264],"category_scores_gemma":[0.005918731,0.0001562016,0.0004981658,0.0006830221,0.0001978844,0.0006828386,0.000422906,0.00078786,0.002778317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003881298,"about_ca_system_score_gemma":0.0008363688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00285203,"about_ca_topic_score_gemma":0.00337803,"domain_scores_codex":[0.9996644,0.0001232303,0.00001575075,0.00006225576,0.00009459676,0.00003971917],"domain_scores_gemma":[0.9992757,0.0003250591,0.00014333,0.00004490243,0.00009052652,0.0001205198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009508906,0.0003587203,0.2208502,0.0005892871,0.0004636565,0.0002537755,0.0001342779,0.009466327,0.002243176,0.01537009,0.2676081,0.4817116],"study_design_scores_gemma":[0.0006039059,0.0007052441,0.4236925,0.0009004275,0.001442651,0.002626183,0.0008635625,0.1359508,0.008217668,0.2884074,0.1364022,0.0001873275],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5463469,0.03961697,0.08780628,0.1558,0.008436023,0.0003423471,0.04251008,0.00413952,0.1150019],"genre_scores_gemma":[0.9175512,0.00782873,0.03404252,0.002855659,0.003209755,0.0001284321,0.009595854,0.0005808366,0.02420707],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01301264,"threshold_uncertainty_score":0.04353166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009869681459001817,"score_gpt":0.3350683097426663,"score_spread":0.3251986282836645,"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."}}