{"id":"W4283065690","doi":"10.3389/fpubh.2022.861067","title":"Influencing Factors of Health Technology Assessment to Orphan Drugs: Empirical Evidence in England, Scotland, Canada, and Australia","year":2022,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orphan drug; Medicine; Health technology; Cost-effectiveness analysis; Cost–benefit analysis; Public economics; Family medicine; Actuarial science; Economic growth; Political science; Health care; Business; Cost effectiveness; Risk analysis (engineering); Economics; Law","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":["metaresearch","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.03713572,0.0004586656,0.001423305,0.005557586,0.002186519,0.005112242,0.001580962,0.0009406691,0.002418364],"category_scores_gemma":[0.2158087,0.0005100819,0.001556366,0.01219286,0.00329194,0.002143854,0.002958987,0.001728649,0.0001104451],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02777676,"about_ca_system_score_gemma":0.0526747,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8393328,"about_ca_topic_score_gemma":0.8330743,"domain_scores_codex":[0.9376912,0.02161026,0.0107087,0.002554704,0.02471619,0.002718917],"domain_scores_gemma":[0.7299722,0.1450967,0.04774413,0.005452199,0.06365795,0.008076751],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001121944,0.0001820304,0.7702136,0.01256143,0.002308504,0.001000038,0.02006857,0.001087991,0.0001930865,0.007431576,0.007141073,0.1766902],"study_design_scores_gemma":[0.0001671832,0.0001859389,0.9481736,0.01119621,0.001282025,0.0005003091,0.01085844,0.001021371,0.0002575737,0.0009540507,0.02526479,0.0001383822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7610823,0.1805616,0.001875737,0.0168293,0.0004097055,0.0009642681,0.001895714,0.00003915657,0.03634221],"genre_scores_gemma":[0.9715356,0.024334,0.001517295,0.001538167,0.00005769264,0.0001021531,0.0003643908,0.00001754457,0.0005331537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9985767,"threshold_uncertainty_score":0.3232267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4374003662971307,"score_gpt":0.4534433820486378,"score_spread":0.01604301575150702,"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."}}