{"id":"W2604950454","doi":"10.1371/journal.pmed.1002277","title":"Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study","year":2017,"lang":"en","type":"article","venue":"PLoS Medicine","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":286,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"National Cancer Institute; National Institutes of Health","keywords":"Medicine; Lung cancer; National Lung Screening Trial; Lung cancer screening; Internal medicine; Cancer; Cancer screening; Oncology; Family history; Retrospective cohort study; Body mass index; Receiver operating characteristic","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":[0.044049,0.001159574,0.000720333,0.001422154,0.0004328353,0.001046785,0.001613143,0.000928472,0.0008569346],"category_scores_gemma":[0.0972535,0.0005567462,0.001368906,0.0008296402,0.0007779667,0.0007899867,0.001024857,0.001485203,0.0004121595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009113586,"about_ca_system_score_gemma":0.001273794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004414912,"about_ca_topic_score_gemma":0.002260623,"domain_scores_codex":[0.9892729,0.007689057,0.0006611323,0.0009747809,0.001131705,0.0002704667],"domain_scores_gemma":[0.876705,0.08953709,0.01120113,0.01202882,0.00936137,0.001166584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001836726,0.0003905708,0.9820622,0.00003833499,0.0005015798,0.0001122108,0.0003132012,0.005642313,0.0001586889,0.000193488,0.0006033138,0.008147538],"study_design_scores_gemma":[0.0007480103,0.004428224,0.7063549,0.0001962278,0.001167585,0.001494183,0.0006319851,0.2797517,0.001274784,0.001443938,0.002389138,0.0001193576],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98981,0.0002933663,0.008613537,0.00008595811,0.00001913166,0.0002137694,0.0005290065,0.00004991317,0.0003853717],"genre_scores_gemma":[0.9955901,0.00008953992,0.003099228,0.00003197236,0.00001288724,0.0001068983,0.0009750834,0.00001435293,0.00008004674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.044049,"threshold_uncertainty_score":0.2329562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.039759819627657,"score_gpt":0.3509640354887633,"score_spread":0.3112042158611062,"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."}}