{"id":"W2355669218","doi":"","title":"Health Technology Assessment and Medical Insurance","year":2002,"lang":"en","type":"article","venue":"Huaxi yixue","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Health insurance; Control (management); Self-insurance; Quality (philosophy); Health technology; China; Medical underwriting; Actuarial science; Health services; Health policy; Health care; Environmental health; Economic growth; Public health; Business; Nursing; Population","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007257293,0.0001493236,0.0008160265,0.0003413108,0.00021846,0.00004463836,0.0002439601,0.0002116262,0.001718244],"category_scores_gemma":[0.001344833,0.0001876907,0.00004634733,0.0002488749,0.0001402376,0.0002191177,0.00007588249,0.0002999292,0.001651937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003539521,"about_ca_system_score_gemma":0.0001158254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003022545,"about_ca_topic_score_gemma":0.0001524902,"domain_scores_codex":[0.9964125,0.0001609315,0.002375976,0.0005039476,0.0001187779,0.0004278444],"domain_scores_gemma":[0.9979596,0.0003158905,0.0009661627,0.0004365276,0.0000278861,0.00029394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001913792,0.0001605915,0.4027371,0.0002545675,0.00004127682,0.000004862634,0.0007148341,0.000007516887,5.818148e-7,0.5103807,0.07665502,0.009040969],"study_design_scores_gemma":[0.00216899,0.0003137201,0.4213107,0.0002453894,0.00000271956,0.0001240306,0.0009769305,0.01955392,0.000002180288,0.03423936,0.5203718,0.0006903231],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3096713,0.0185688,0.004672176,0.6481839,0.0008308667,0.0007206075,0.0001695829,0.000224412,0.01695834],"genre_scores_gemma":[0.9715161,0.001678505,0.003272519,0.02247773,0.0002118659,0.00008264321,0.000007980146,0.00002525792,0.0007274357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6618447,"threshold_uncertainty_score":0.9991943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3697993201489312,"score_gpt":0.4691279527920864,"score_spread":0.09932863264315517,"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."}}