{"id":"W4396862807","doi":"10.1177/0272989x241249182","title":"The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations","year":2024,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canadian Partnership Against Cancer","funders":"National Cancer Institute; Erasmus Universitair Medisch Centrum Rotterdam; Health Canada; Cancer Australia; Partenariat Canadien Contre Le Cancer; Universität Zürich; Centre Hospitalier Universitaire Vaudois; ZonMw; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Institutes of Health; Cancer Research UK; Teva Pharmaceutical Industries","keywords":"Lung cancer; Medicine; Lung cancer screening; Cancer; Stage (stratigraphy); Incidence (geometry); Epidemiology; Internal medicine; Oncology; Demography; Biology; Mathematics","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":[0.02500054,0.001317551,0.001293806,0.0007623626,0.0008736723,0.002487415,0.002617666,0.002010631,0.002655814],"category_scores_gemma":[0.08608794,0.00103044,0.002014261,0.0005216032,0.0009838204,0.002525164,0.001316713,0.002530444,0.00031855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004784795,"about_ca_system_score_gemma":0.003416683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02883509,"about_ca_topic_score_gemma":0.01785105,"domain_scores_codex":[0.9879079,0.009236969,0.0004357247,0.001010716,0.000762757,0.0006458859],"domain_scores_gemma":[0.8889989,0.09969265,0.005088239,0.002505004,0.00308185,0.0006333382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003735933,0.00008119255,0.01482578,0.00009067416,0.0002148777,0.00007931589,0.0000912969,0.9780467,0.0002528305,0.002685229,0.0004382844,0.002820112],"study_design_scores_gemma":[0.0001533911,0.0003724559,0.00721644,0.0001432598,0.0003312948,0.00008367845,0.0002154185,0.9811248,0.0007836061,0.008452323,0.001054771,0.00006871389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8955769,0.001000381,0.08366323,0.003662786,0.0001541503,0.0005283074,0.003294586,0.0004148374,0.01170472],"genre_scores_gemma":[0.9876457,0.0002123026,0.01000674,0.0004518574,0.00002197724,0.0002166407,0.0008093558,0.00004726913,0.0005880999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02883509,"threshold_uncertainty_score":0.1322171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06180540773436391,"score_gpt":0.4747675484882615,"score_spread":0.4129621407538976,"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."}}