{"id":"W2883096394","doi":"10.1186/s12913-018-3369-2","title":"Understanding reasons for unmet health care needs in Korea: what are health policy implications?","year":2018,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Wonkwang University","keywords":"Medicine; Socioeconomic status; Nursing research; Health care; Health administration; Public health; Environmental health; Health informatics; Health policy; Needs assessment; Odds; Health services research; Population; Logistic regression; National Health and Nutrition Examination Survey; Gerontology; Nursing; Economic growth","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.008344201,0.0002813787,0.001075937,0.002577202,0.001809523,0.0003502354,0.0006693317,0.0002557897,0.00002595696],"category_scores_gemma":[0.00008726014,0.0002740851,0.0001387931,0.003402738,0.0001553685,0.0006385721,0.0001881186,0.0005643664,0.0001816724],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00846559,"about_ca_system_score_gemma":0.004037257,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1358494,"about_ca_topic_score_gemma":0.1112372,"domain_scores_codex":[0.9940618,0.0004249637,0.001915223,0.0008929494,0.0002360875,0.002468972],"domain_scores_gemma":[0.9963688,0.000200295,0.0009570085,0.001021758,0.0003436023,0.001108576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001734061,0.0002934765,0.3308533,0.02449205,0.00004685494,9.140917e-7,0.08364779,0.00002190351,7.711816e-7,0.5258083,0.002540111,0.0321211],"study_design_scores_gemma":[0.00245249,0.002415998,0.5006969,0.003349042,5.920631e-7,0.00001561318,0.2548905,0.001043432,0.000002882913,0.03339899,0.2010831,0.0006504947],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1801025,0.179897,0.02331307,0.5768396,0.003516933,0.02317135,0.004720874,0.0005238747,0.007914791],"genre_scores_gemma":[0.9777057,0.009697105,0.001314048,0.008862164,0.001273503,0.0005140199,0.000233776,0.00009861144,0.0003011314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7976031,"threshold_uncertainty_score":0.9999712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2883959747306007,"score_gpt":0.4559961364563662,"score_spread":0.1676001617257654,"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."}}