{"id":"W3142649038","doi":"","title":"The NICE Cost-Effectiveness Threshold: What it is and What that Means","year":2008,"lang":"en","type":"article","venue":"MPRA Paper","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nice; Excellence; Reimbursement; Equity (law); Actuarial science; Cost effectiveness; Health technology; Psychological intervention; Economics; Medicine; Business; Health care; Public economics; Risk analysis (engineering); Computer science; Political science; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009362234,0.0002370252,0.0006796309,0.0001055554,0.0008262075,0.0007537857,0.0003237912,0.0001722177,0.0005111893],"category_scores_gemma":[0.0006084723,0.0002274247,0.0001211521,0.0001393115,0.0002255467,0.004355849,0.0000968676,0.0002286256,0.001881106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002760367,"about_ca_system_score_gemma":0.00008586268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002414521,"about_ca_topic_score_gemma":0.0002602024,"domain_scores_codex":[0.9969727,0.0003210547,0.001465221,0.0006227565,0.0001278336,0.0004904466],"domain_scores_gemma":[0.996091,0.002218798,0.0007215866,0.0007256518,0.00005874879,0.0001841892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002783977,0.0004954864,0.295578,0.001181837,0.0009734207,0.00003153184,0.05321799,0.0004926229,0.00005623726,0.1912964,0.4297791,0.026619],"study_design_scores_gemma":[0.0009328961,0.00005516451,0.06098981,0.0001758196,0.000009034583,0.00003642515,0.00669063,0.001051303,0.00003146303,0.006114149,0.9235138,0.0003994961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6060249,0.09691033,0.0006353661,0.2769098,0.003670611,0.002916569,0.00009429347,0.000121066,0.01271704],"genre_scores_gemma":[0.8166587,0.07670249,0.0002136206,0.1023453,0.0004694423,0.0005425476,0.00002054917,0.00008051087,0.002966806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4937347,"threshold_uncertainty_score":0.9988961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4012173657302667,"score_gpt":0.4189184831127356,"score_spread":0.01770111738246893,"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."}}