{"id":"W3035148408","doi":"10.1111/all.14444","title":"SF‐6Dv2 preference value set for health utility in food allergy","year":2020,"lang":"en","type":"article","venue":"Allergy","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Institut Universitaire en Santé Mentale de Québec; Université de Montréal","funders":"Canadian Allergy, Asthma and Immunology Foundation","keywords":"Preference; EQ-5D; Medicine; Quality of life (healthcare); Population; Set (abstract data type); Time-trade-off; Cohort; Food allergy; Dimension (graph theory); Quality-adjusted life year; Demography; Allergy; Statistics; Environmental health; Health related quality of life; Mathematics; Computer science; Cost effectiveness; Internal medicine; Immunology; Risk analysis (engineering)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006400143,0.0002544821,0.001152322,0.0001700967,0.0001556178,0.00005664765,0.0004663781,0.0001771282,0.0004033549],"category_scores_gemma":[0.001930448,0.0003453448,0.0001589738,0.0002527525,0.00005031032,0.0003372018,0.0000964102,0.0002139556,0.0006123994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003853122,"about_ca_system_score_gemma":0.0003814032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001925998,"about_ca_topic_score_gemma":0.003060132,"domain_scores_codex":[0.9943001,0.0003372264,0.003653364,0.0009207546,0.00009766121,0.0006909054],"domain_scores_gemma":[0.9969614,0.0006690936,0.001376865,0.0005249994,0.0000498769,0.0004177371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002217363,0.000373815,0.00816352,0.001403492,0.000420719,0.000001561328,0.01742095,0.00226562,0.000004463584,0.7115695,0.2565376,0.001617038],"study_design_scores_gemma":[0.0019955,0.0006124126,0.03112167,0.00006275244,9.402254e-7,0.000001427201,0.0007511812,0.03686637,0.000007528291,0.02481726,0.9032795,0.0004834323],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3067118,0.01188419,0.03690721,0.6213307,0.001814414,0.004876109,0.004015873,0.0003933602,0.01206632],"genre_scores_gemma":[0.9290822,0.0004502119,0.003831449,0.06545484,0.0004049754,0.0003335427,0.0001957043,0.0000537527,0.000193306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6867523,"threshold_uncertainty_score":0.9998999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5724675847802668,"score_gpt":0.4312859822202083,"score_spread":0.1411816025600586,"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."}}