{"id":"W2807835500","doi":"10.21037/tlcr.2018.06.03","title":"Selecting lung cancer screenees using risk prediction models—where do we go from here","year":2018,"lang":"en","type":"review","venue":"Translational Lung Cancer Research","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Medicine; Lung cancer; National Lung Screening Trial; Lung cancer screening; Medicaid; Interim; Risk assessment; Cancer; Incidence (geometry); Internal medicine; Emergency medicine; Health care","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009835946,0.0007563126,0.001757374,0.0005929508,0.0007868512,0.0001885772,0.0003693668,0.0005846646,0.002109498],"category_scores_gemma":[0.00003137084,0.0006211005,0.0007339333,0.001357148,0.0002305602,0.0003551906,0.00008202297,0.001868649,0.0000283226],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004425649,"about_ca_system_score_gemma":0.005225058,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02085466,"about_ca_topic_score_gemma":0.005045435,"domain_scores_codex":[0.9933751,0.0006505039,0.001072123,0.001519211,0.002349241,0.00103388],"domain_scores_gemma":[0.996711,0.0008102974,0.0003948052,0.0006943083,0.0009670016,0.0004226149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005951035,0.0004650748,0.04506087,0.04479267,0.01001431,0.00006139324,0.001238063,0.004577895,0.000005910696,0.000223619,0.0194868,0.8734783],"study_design_scores_gemma":[0.00298594,0.0002119863,0.0006158382,0.1691423,0.01152772,0.00003042442,0.00006523696,0.0634239,0.00001575846,0.0005145822,0.750555,0.0009112726],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006600677,0.9876335,0.0005329175,0.0006617214,0.0005496222,0.003557797,0.005436885,0.0001312851,0.0008362186],"genre_scores_gemma":[0.00178305,0.9891847,0.001064552,0.00001377113,0.004391455,0.002151009,0.0005934626,0.0002515541,0.0005663891],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.872567,"threshold_uncertainty_score":0.999624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1663947614334943,"score_gpt":0.4854986603865147,"score_spread":0.3191038989530204,"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."}}