{"id":"W2895837946","doi":"10.3390/ijerph15102265","title":"Prediction and Decomposition of Efficiency Differences in Chinese Provincial Community Health Services","year":2018,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"National Office for Philosophy and Social Sciences; Ministry of Education of the People's Republic of China","keywords":"Data envelopment analysis; Theil index; Index (typography); Pace; Health care; Community health; Restructuring; Service (business); Business; Economic growth; China; Geography; Economics; Statistics; Marketing; Computer science; Mathematics; Finance","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":[0.004301669,0.00006187908,0.0002487413,0.000492011,0.000182178,0.00004992578,0.0001989369,0.0000446789,0.00002975074],"category_scores_gemma":[0.00005122347,0.00004832291,0.0000227428,0.0001108272,0.0002183615,0.000312591,0.00009325028,0.0003415092,0.000002671187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003624806,"about_ca_system_score_gemma":0.0001441979,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01214349,"about_ca_topic_score_gemma":0.001765306,"domain_scores_codex":[0.9984666,0.0001987349,0.0007835164,0.0001076504,0.0002086577,0.000234848],"domain_scores_gemma":[0.9991136,0.00005377497,0.0004690544,0.00007227346,0.00005565035,0.0002356045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005083753,0.0005245138,0.9609854,0.0001171007,0.00001911365,0.000001134926,0.004002433,2.421808e-7,0.00003255147,0.001115931,0.000008049536,0.03314266],"study_design_scores_gemma":[0.000501472,0.0017099,0.9924194,0.0001092031,7.294172e-8,0.00003398163,0.001462641,0.0002461525,0.000003107404,0.002977633,0.0005047437,0.00003168115],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941961,0.001582714,0.0001784081,0.003273842,0.0002235192,0.0001463752,0.0001848848,0.000001688777,0.0002124478],"genre_scores_gemma":[0.9969915,0.002577968,0.00007274747,0.0001381371,0.0001892971,0.000002216283,0.00001115963,0.00000443243,0.00001256807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03311098,"threshold_uncertainty_score":0.9944347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07113453825642557,"score_gpt":0.3562870502330795,"score_spread":0.2851525119766539,"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."}}