{"id":"W2298541750","doi":"10.1016/j.jtho.2016.01.021","title":"Computer Vision Tool and Technician as First Reader of Lung Cancer Screening CT Scans","year":2016,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency; Princess Margaret Cancer Centre; University of Calgary; University of Ottawa; Juravinski Hospital; Memorial University of Newfoundland; Vancouver Coastal Health; Institut universitaire de cardiologie et de pneumologie de Québec; University Health Network; Ottawa Hospital; Dalhousie University; Brock University; Toronto General Hospital","funders":"Partenariat Canadien Contre Le Cancer; Terry Fox Research Institute","keywords":"Technician; Medicine; Lung cancer; Radiology; Lung cancer screening; Confidence interval; Computed tomography; Medical physics; Nuclear medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00406422,0.0009590956,0.0008947043,0.004136564,0.0008400921,0.001668935,0.001267264,0.001874356,0.03003707],"category_scores_gemma":[0.02529179,0.0006884565,0.001001997,0.0007695085,0.0004015779,0.001898635,0.0009018123,0.001704524,0.01005616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000670232,"about_ca_system_score_gemma":0.001587728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001624529,"about_ca_topic_score_gemma":0.002087774,"domain_scores_codex":[0.9948328,0.001802614,0.000770807,0.001374267,0.0007669801,0.0004525637],"domain_scores_gemma":[0.9823887,0.007805812,0.00115781,0.001173848,0.005965282,0.001508593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003379401,0.003135948,0.2847558,0.00130966,0.0003822063,0.01703718,0.003217718,0.001756781,0.05563588,0.001353788,0.08832557,0.53971],"study_design_scores_gemma":[0.0007528584,0.008156889,0.5012826,0.001534061,0.001339189,0.1592107,0.01090336,0.06111657,0.1348329,0.003393867,0.116515,0.0009619605],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7279679,0.007459435,0.1625086,0.0168163,0.006311203,0.001938281,0.004082493,0.009579848,0.06333603],"genre_scores_gemma":[0.8160883,0.001909922,0.1457932,0.004266995,0.001126516,0.0008269755,0.001302191,0.00050625,0.02817958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03003707,"threshold_uncertainty_score":0.100484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801706518436059,"score_gpt":0.4195248642971166,"score_spread":0.401507799112756,"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."}}