{"id":"W4409329675","doi":"10.1001/jamaoncol.2025.0473","title":"National Cancer System Characteristics and Global Pan-Cancer Outcomes","year":2025,"lang":"en","type":"article","venue":"JAMA Oncology","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Cancer Institute","keywords":"Medicine; Demography; Population; Per capita; Human Development Index; Gross domestic product; Cancer; Gross national income; Gerontology; Environmental health; Human development (humanity); Economic growth; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003321773,0.0001608817,0.0006312118,0.0001170146,0.0001075758,0.00007955422,0.0001739533,0.0002654177,0.0002096467],"category_scores_gemma":[0.0001884342,0.0001772423,0.00008087654,0.0001523644,0.0001072413,0.0002285392,0.00009173912,0.0001498223,0.0001281409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564405,"about_ca_system_score_gemma":0.0003474663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001315985,"about_ca_topic_score_gemma":0.000458442,"domain_scores_codex":[0.9987122,0.00001441092,0.0005890462,0.0003617087,0.00002779308,0.0002947983],"domain_scores_gemma":[0.9992434,0.00009178087,0.000359856,0.0001379487,0.00009545573,0.00007155223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003321011,0.00003103367,0.4788987,0.0000506559,0.00009548281,0.000002560506,0.00004106701,0.00000610433,0.000001643366,0.4725339,0.008743337,0.03956237],"study_design_scores_gemma":[0.0007418991,0.00002761941,0.6474763,0.0000282431,0.00001128278,0.000002471845,0.00003205882,0.0004491728,0.000002673373,0.009895707,0.3411965,0.0001361061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6216911,0.009352584,0.001137155,0.02326657,0.005949373,0.0003890072,0.002771382,0.00009731595,0.3353455],"genre_scores_gemma":[0.9895288,0.00130061,0.0001853358,0.00552029,0.0004047196,0.0001500304,0.00001017308,0.00001100736,0.002889088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4626381,"threshold_uncertainty_score":0.722773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02895249680210092,"score_gpt":0.3086793287352443,"score_spread":0.2797268319331433,"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."}}