{"id":"W3145866246","doi":"10.1002/ijc.33578","title":"Personalising lung cancer screening: An overview of risk‐stratification opportunities and challenges","year":2021,"lang":"en","type":"review","venue":"International Journal of Cancer","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"National Cancer Institute; Horizon 2020 Framework Programme","keywords":"Lung cancer screening; Medicine; Lung cancer; Cancer screening; Population; Risk stratification; Risk assessment; Intensive care medicine; Risk analysis (engineering); Cancer; Environmental health; Oncology; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004502424,0.001014482,0.002622702,0.002894449,0.0003359168,0.001507221,0.001293776,0.002094455,0.003037471],"category_scores_gemma":[0.007545145,0.0005035925,0.002207433,0.002715674,0.0007375213,0.001762248,0.0008523417,0.002720031,0.0007332363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00146627,"about_ca_system_score_gemma":0.002816841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002255458,"about_ca_topic_score_gemma":0.00385255,"domain_scores_codex":[0.9982193,0.000740795,0.0003274758,0.0001937748,0.0004366795,0.00008194307],"domain_scores_gemma":[0.9919657,0.007047135,0.0003388932,0.00008736783,0.0004654393,0.00009554096],"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":[0.0001023686,0.00006810378,0.0002411833,0.1116459,0.0004267403,0.00007954313,0.00009731868,0.0004788462,0.0002601819,0.004285301,0.0103994,0.8719151],"study_design_scores_gemma":[0.0001220397,0.0004567365,0.00289997,0.1773993,0.001866932,0.001578129,0.0002649822,0.0005135451,0.0004003539,0.009228311,0.8051883,0.00008144417],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003596772,0.9992531,0.00008411071,0.0003921959,0.00005091201,0.000006645559,0.000008353223,0.000002387799,0.0001662878],"genre_scores_gemma":[0.0004399964,0.999055,0.0002028943,0.0001693769,0.00006366277,0.00001228361,0.000009700431,9.350007e-7,0.00004625346],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004502424,"threshold_uncertainty_score":0.0238114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3573408766132797,"score_gpt":0.4915044598762989,"score_spread":0.1341635832630191,"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."}}