{"id":"W3006043108","doi":"10.21037/qims.2020.01.08","title":"Lung cancer screening: how do we make it better?","year":2020,"lang":"en","type":"letter","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cancer; Lung cancer; Computer science; Medicine; Intensive care medicine; Data science; Pathology; 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":[0.01029238,0.001105588,0.002365387,0.00174974,0.006403606,0.007316507,0.00243591,0.07652689,0.01038431],"category_scores_gemma":[0.04741907,0.001030142,0.00186913,0.0009688972,0.007429849,0.01132014,0.003386607,0.06459174,0.007054069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009526017,"about_ca_system_score_gemma":0.01258124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01027848,"about_ca_topic_score_gemma":0.01827453,"domain_scores_codex":[0.9913675,0.00321692,0.001039947,0.0008221691,0.002513161,0.00104027],"domain_scores_gemma":[0.9682873,0.01462162,0.001931202,0.0007830398,0.006160886,0.008215861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000053426,0.00008192037,0.001563574,0.0001414959,0.00003220978,0.001618355,0.0001462125,0.00008353937,0.0002373695,0.006743228,0.963676,0.02562252],"study_design_scores_gemma":[0.000191775,0.0001294949,0.002191024,0.001567057,0.00007786351,0.00526912,0.001021575,0.0007602086,0.0002315804,0.04121683,0.9471794,0.0001640582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00005746044,0.001208813,0.00003893831,0.9933977,0.004550218,0.000002335855,0.000006076871,0.000005160846,0.0007332811],"genre_scores_gemma":[0.00159316,0.002152059,0.0003064634,0.9467547,0.04699324,0.00001619048,0.00001360559,0.00001378413,0.002156753],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07652689,"threshold_uncertainty_score":0.06911641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07107447885007556,"score_gpt":0.3627558899381253,"score_spread":0.2916814110880497,"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."}}