{"id":"W6963032582","doi":"10.17632/p45pfscm8n","title":"2015 Jakarta's Health Insurance Claim Data","year":2021,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"Security, Politics, and Digital Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Currency; Liberian dollar; National health insurance; Health insurance; Payment; General insurance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007863067,0.0009009092,0.001012022,0.005299358,0.0008734809,0.002596218,0.001400765,0.0009511903,0.04212847],"category_scores_gemma":[0.007671155,0.0004962083,0.0006834177,0.01089108,0.0003345323,0.001048148,0.001555997,0.001532084,0.04820251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002824718,"about_ca_system_score_gemma":0.004298518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1231677,"about_ca_topic_score_gemma":0.1672458,"domain_scores_codex":[0.9991199,0.00009889639,0.0001552459,0.0001988001,0.0002566675,0.0001704972],"domain_scores_gemma":[0.9976763,0.0004884354,0.0003539067,0.0003615322,0.000862497,0.0002572892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001261915,0.00003226852,0.006918018,0.0004890323,0.00004522265,0.00005535662,0.00006544205,0.000327805,0.00008270411,0.001152847,0.9867775,0.003927784],"study_design_scores_gemma":[0.000142079,0.00001582191,0.07273813,0.0008353646,0.00005388021,0.0001338194,0.0004729548,0.0009534865,0.0005437812,0.001225234,0.9228168,0.00006872194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004471945,0.00006225557,0.00001715325,0.00007289535,0.0000141845,0.000006685978,0.99852,0.00006003235,0.0007996493],"genre_scores_gemma":[0.00167511,0.00009080759,0.0001348076,0.00004331199,0.000009639284,0.00005452497,0.9966515,0.00002772242,0.001312552],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1231677,"threshold_uncertainty_score":0.2449015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.249525391307726,"score_gpt":0.4593355938405076,"score_spread":0.2098102025327817,"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."}}