{"id":"W2914494683","doi":"10.5539/ass.v15n2p90","title":"Factors Associated to the Enrollment in Health Insurance: An Experience from Selected Districts of Nepal","year":2019,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University Grants Commission","keywords":"Preparedness; Schedule; Health care; Health insurance; Psychology; Medicine; Demography; Political science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004745595,0.0002166519,0.0002845264,0.0004463441,0.00121837,0.0007138267,0.0003767081,0.0004547739,0.001584217],"category_scores_gemma":[0.001082162,0.00029931,0.0002153043,0.0006485098,0.000587625,0.000652545,0.001089186,0.0004934046,0.0002692947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005834106,"about_ca_system_score_gemma":0.0008474959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01698556,"about_ca_topic_score_gemma":0.03642618,"domain_scores_codex":[0.9996541,0.0001340967,0.00001981359,0.00004135908,0.00003769732,0.0001130818],"domain_scores_gemma":[0.9994622,0.0001670454,0.0001107161,0.00002974369,0.00007062026,0.0001597014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001508276,0.000753035,0.8417182,0.0002309062,0.00003992332,0.007779388,0.1258233,0.0001178316,0.002212006,0.0001904861,0.000879753,0.0201043],"study_design_scores_gemma":[0.00001036936,0.0009806153,0.8729427,0.0000554603,0.0000291668,0.0029964,0.1194458,0.0001861143,0.0003102731,0.00006977947,0.002944653,0.00002867368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999463,0.00004425646,0.00002708934,0.00004649299,0.000001067194,0.00001651053,0.00004930169,9.211619e-7,0.000351372],"genre_scores_gemma":[0.9987651,0.000223158,0.0001085724,0.00009108978,0.000003808667,0.00003430777,0.00008863516,0.000001549112,0.0006837763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01698556,"threshold_uncertainty_score":0.03377342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04671659644231397,"score_gpt":0.288361336996842,"score_spread":0.2416447405545281,"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."}}