{"id":"W3012466664","doi":"10.1111/cts.12778","title":"Reimbursement Lag of New Drugs Under Taiwan's National Health Insurance System Compared With United Kingdom, Canada, Australia, Japan, and South Korea","year":2020,"lang":"en","type":"article","venue":"Clinical and Translational Science","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Health Insurance Administration; National Taiwan University","keywords":"Reimbursement; National health insurance; Medicine; Health insurance; Environmental health; Time lag; Family medicine; Lag; Economic growth; Health care; Economics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00276155,0.0001757183,0.0003209034,0.001414448,0.0003436913,0.001170443,0.0003499717,0.0002987646,0.002140698],"category_scores_gemma":[0.01203867,0.00015958,0.001253766,0.002639473,0.0002914117,0.0008897416,0.000908179,0.0006657648,0.000191696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003040943,"about_ca_system_score_gemma":0.005865692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0662412,"about_ca_topic_score_gemma":0.07096744,"domain_scores_codex":[0.9971167,0.0005364427,0.0008772814,0.0004644504,0.0004864475,0.0005188342],"domain_scores_gemma":[0.9847403,0.002625563,0.009213386,0.0004920879,0.001627041,0.001301675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002882432,0.00004757112,0.9772504,0.0003487445,0.000227767,0.0003300869,0.0003312395,0.0007308158,0.0003965042,0.0005558094,0.001646372,0.01784654],"study_design_scores_gemma":[0.00003201239,0.0001307952,0.9915963,0.0001147963,0.0001840214,0.0005057586,0.0005449962,0.001378271,0.000424603,0.0001029773,0.004964952,0.00002046118],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853813,0.005609683,0.0007120396,0.001622946,0.00004922573,0.00005645071,0.004160413,0.00002762954,0.002380392],"genre_scores_gemma":[0.9938803,0.001509214,0.0004618325,0.0003347079,0.00004284334,0.00004882883,0.00305651,0.00001033568,0.0006553394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9337588,"threshold_uncertainty_score":0.1317113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1646822195266346,"score_gpt":0.3239617594046584,"score_spread":0.1592795398780237,"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."}}