{"id":"W2765688979","doi":"10.1016/j.jval.2017.08.941","title":"Time to Access: Too Fast, Too Slow, or Just Right? An Evolving Public Reimbursement Landscape of Drugs For Rare Diseases In Canada","year":2017,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Reimbursement; Medicine; Negotiation; Orphan drug; Alliance; Market access; Public economics; Actuarial science; Business; Economic growth; Political science; Health care; Law; Bioinformatics; Economics","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":[0.007790095,0.0002177281,0.0009615174,0.002912685,0.00529822,0.00992937,0.002281116,0.002346735,0.006273156],"category_scores_gemma":[0.03438781,0.00038248,0.000817948,0.006557915,0.004100013,0.00263334,0.001975103,0.004811609,0.0001828059],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1923119,"about_ca_system_score_gemma":0.2842626,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941573,"about_ca_topic_score_gemma":0.9970847,"domain_scores_codex":[0.9880641,0.001601658,0.0006584116,0.0007159351,0.005237928,0.003721878],"domain_scores_gemma":[0.9324461,0.01240513,0.006144265,0.0006330385,0.02692891,0.0214425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001127659,0.0003534771,0.3135584,0.001053344,0.0003749992,0.001768438,0.008648665,0.006793988,0.001311498,0.2047291,0.2082412,0.2520394],"study_design_scores_gemma":[0.000346532,0.0001995435,0.7152095,0.003008998,0.0004360933,0.001155414,0.02195091,0.01285614,0.0007102035,0.02977317,0.213759,0.0005945169],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.260523,0.02567172,0.001199827,0.6689966,0.0008423102,0.00009159056,0.003950515,0.00005045883,0.03867409],"genre_scores_gemma":[0.9572376,0.01255185,0.001470369,0.02295903,0.0004974899,0.00003157329,0.0008203399,0.00007248791,0.004359241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8076881,"threshold_uncertainty_score":0.9368037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3501421731611019,"score_gpt":0.424691304518594,"score_spread":0.07454913135749214,"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."}}