{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004101059,0.0006515951,0.001858345,0.0007298265,0.00009948226,0.00007182797,0.0001117536,0.000216377,0.0003059236],"category_scores_gemma":[0.0004144772,0.0004936442,0.0002510285,0.0004994381,0.0004516786,0.0001231952,0.0000664167,0.001564039,0.000006837644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002731949,"about_ca_system_score_gemma":0.0002754927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006634736,"about_ca_topic_score_gemma":0.00004480787,"domain_scores_codex":[0.9967495,0.0002155787,0.0006254704,0.0009897,0.0007644258,0.0006553695],"domain_scores_gemma":[0.9966243,0.002277322,0.0003370805,0.0003677481,0.0001824452,0.0002111369],"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":[0.00006888883,0.00002784948,0.2249648,0.001419563,0.0003441639,0.007549871,0.001098718,3.262489e-7,0.00001174398,0.00001349347,0.747354,0.01714662],"study_design_scores_gemma":[0.001720157,0.0001326753,0.01063496,0.01838809,0.0009442484,0.00008134935,0.0009858909,0.0005358315,0.00001519935,0.0001221275,0.96592,0.0005194651],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001555949,0.08107532,0.0002336154,0.9152133,0.0007171657,0.000558123,0.00005719589,0.00006970282,0.0005195782],"genre_scores_gemma":[0.009608379,0.03795234,0.0009959158,0.945958,0.003984012,0.0003312276,0.0003381391,0.0001455882,0.0006863974],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.218566,"threshold_uncertainty_score":0.9997515,"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."}}