{"id":"W2966239700","doi":"10.1136/thoraxjnl-2019-213156","title":"Lung cancer screening: enhancing risk stratification and minimising harms by incorporating information from screening results","year":2019,"lang":"en","type":"letter","venue":"Thorax","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Lung cancer screening; Risk stratification; Cancer screening; Lung cancer; Risk assessment; Environmental health; Cancer; Intensive care medicine; Oncology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000397148,0.0004499447,0.0006415716,0.0001775026,0.000228996,0.0002697337,0.0001175376,0.0005694206,0.00004811757],"category_scores_gemma":[0.0001443702,0.0003978881,0.0001068554,0.0001798613,0.00005404132,0.0005856547,0.00006749629,0.001178505,0.00001801043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003787403,"about_ca_system_score_gemma":0.0001984218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006050121,"about_ca_topic_score_gemma":0.0001136068,"domain_scores_codex":[0.9974612,0.0001187143,0.0008610665,0.0005978012,0.0005946549,0.000366543],"domain_scores_gemma":[0.9975278,0.0003977273,0.001237341,0.0005479247,0.0001906645,0.00009853945],"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":[0.000292905,0.00002754817,0.01916382,0.0006210908,0.0006584603,0.0000281216,0.001348204,0.00006526305,0.0005413015,0.000002078785,0.8901957,0.08705556],"study_design_scores_gemma":[0.01957838,0.001087186,0.05330102,0.02986506,0.009789188,0.00004703246,0.001832665,0.04096128,0.03297986,0.0001909792,0.8067438,0.003623558],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1717036,0.01840195,0.05050012,0.7347003,0.002135145,0.006817665,0.009861621,0.0006786349,0.005200933],"genre_scores_gemma":[0.5380825,0.004511977,0.06511629,0.3089813,0.01194095,0.0008383134,0.06740835,0.0004035372,0.002716832],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.425719,"threshold_uncertainty_score":0.9998473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01819772677230509,"score_gpt":0.2949657583280433,"score_spread":0.2767680315557382,"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."}}