{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001612023,0.0001882243,0.0004071394,0.004590977,0.0007366237,0.001494813,0.001140936,0.0005048463,0.002225889],"category_scores_gemma":[0.008423302,0.0004329584,0.0005900523,0.01179792,0.0003580744,0.001580904,0.00155111,0.0006251804,0.0004788043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002649902,"about_ca_system_score_gemma":0.003863208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1004589,"about_ca_topic_score_gemma":0.1087073,"domain_scores_codex":[0.9974801,0.0005921943,0.0009995735,0.0002778043,0.0003347595,0.000315585],"domain_scores_gemma":[0.9919339,0.002198548,0.003320144,0.0004858307,0.001337677,0.0007239015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007626626,0.00006363334,0.9935441,0.0001131681,0.00007583162,0.00009006061,0.0009255056,0.0001113797,0.00006403732,0.00006227824,0.0006322451,0.004241569],"study_design_scores_gemma":[0.00001461826,0.0001077622,0.9900449,0.00009066897,0.00007796649,0.0002430995,0.007354431,0.0006669377,0.0001409001,0.00003825402,0.001198167,0.00002233747],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819294,0.0002310426,0.0001294349,0.0003846799,0.000003496746,0.0001314512,0.0159097,0.00002025738,0.001260559],"genre_scores_gemma":[0.9858971,0.0004346738,0.0009283695,0.0001233454,0.000007585199,0.0002498551,0.01197245,0.000009129954,0.0003773488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1004589,"threshold_uncertainty_score":0.1997483,"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."}}