{"id":"W2966744389","doi":"10.1016/j.vhri.2019.07.001","title":"Tackling the 3 Big Challenges Confronting Health Technology Assessment Development in Asia: A Commentary","year":2019,"lang":"en","type":"article","venue":"Value in Health Regional Issues","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Department for International Development, UK Government; National University of Singapore; Thailand Research Fund; Rockefeller Foundation; Department for International Development; Bill and Melinda Gates Foundation","keywords":"Reimbursement; Health technology; Health care; Political science; Medicine; Economic growth; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07592416,0.001230504,0.002795345,0.003193328,0.005513613,0.01290564,0.008150009,0.04968363,0.007919773],"category_scores_gemma":[0.2090179,0.001262325,0.004044851,0.004981433,0.01642119,0.02270277,0.009184737,0.06580301,0.001914748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02311351,"about_ca_system_score_gemma":0.06114579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03255204,"about_ca_topic_score_gemma":0.03718284,"domain_scores_codex":[0.9557709,0.02433221,0.007430929,0.002711738,0.006842562,0.002911672],"domain_scores_gemma":[0.5999406,0.3245732,0.01269534,0.003563398,0.04576758,0.01346002],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001232629,0.00005014224,0.0008272287,0.004316254,0.0001410497,0.0009422949,0.005292555,0.0003027886,0.0001380832,0.02972709,0.9213903,0.03674897],"study_design_scores_gemma":[0.0001360251,0.0001132112,0.001783535,0.02930709,0.0002332174,0.001211328,0.01068507,0.0004596799,0.0002639742,0.03094274,0.9246321,0.0002320183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001166259,0.01192237,0.00006796415,0.9799867,0.007422144,0.000003987916,0.00001828159,0.00000422041,0.0004576286],"genre_scores_gemma":[0.005023093,0.01503707,0.0002874522,0.9581382,0.02088732,0.00003208895,0.00002247587,0.00002595363,0.0005463861],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9240758,"threshold_uncertainty_score":0.4015301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4292718030615603,"score_gpt":0.4692727845305682,"score_spread":0.04000098146900793,"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."}}