{"id":"W3037518491","doi":"10.1016/j.jcpo.2020.100243","title":"Patterns of cancer care in Sri Lanka: Assessing care provision and unmet needs through an electronic database","year":2020,"lang":"en","type":"article","venue":"Journal of Cancer Policy","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Ministry of Science,Technology and Research","keywords":"Medicine; Cancer registry; Sri lanka; Cancer; Family medicine; Cohort; Health care; Colorectal cancer; Breast cancer; Database; Internal medicine; Economic growth; Socioeconomics","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":[0.0001103361,0.0001555054,0.000473839,0.0001898173,0.00004078712,0.00003195367,0.000144094,0.00007280757,0.00004369003],"category_scores_gemma":[0.00007091096,0.0001265844,0.00007885745,0.0004698784,0.0000314853,0.0007277621,0.00005295825,0.0004573942,2.32903e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006612911,"about_ca_system_score_gemma":0.00213284,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02404645,"about_ca_topic_score_gemma":0.005825634,"domain_scores_codex":[0.9985459,0.00005604994,0.0004627155,0.0001622577,0.0004473864,0.0003256359],"domain_scores_gemma":[0.998927,0.00001957774,0.000372555,0.0001462275,0.0003274349,0.0002071938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001028437,0.00004027973,0.8490056,0.001193394,0.0001191828,0.0001393446,0.06223891,0.0005476864,0.01477698,0.0001961317,0.0001930515,0.07052099],"study_design_scores_gemma":[0.01659184,0.008026259,0.6146384,0.01218604,0.001295573,0.0003325725,0.2365658,0.0006040237,0.05337151,0.0001457778,0.05520295,0.001039332],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603103,0.0349375,0.00007725473,0.004087004,0.00007249136,0.0001551562,0.00009058128,0.000007381108,0.000262366],"genre_scores_gemma":[0.9903699,0.005610354,0.0002810143,0.002502831,0.001196808,0.000005818817,0.00001253761,0.00001726013,0.000003507994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2343672,"threshold_uncertainty_score":0.9824525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06108348869321089,"score_gpt":0.434897330876721,"score_spread":0.3738138421835101,"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."}}