{"id":"W3006106964","doi":"10.1016/j.anai.2020.01.030","title":"Development and acceptability of a shared decision-making tool for commercial peanut allergy therapies","year":2020,"lang":"en","type":"article","venue":"Annals of Allergy Asthma & Immunology","topic":"Patient-Provider Communication in Healthcare","field":"Health Professions","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"National Center for Complementary and Integrative Health; Genentech; National Institutes of Health; Immune Tolerance Network; Genzyme; Baxalta; American Academy of Arts and Sciences; AstraZeneca; Abbott Laboratories; Regeneron Pharmaceuticals; Teva Pharmaceutical Industries; Novartis; De Blindas Vänner; Food Allergy Research and Education; Pfizer; Agency for Healthcare Research and Quality; Sanofi","keywords":"Decision aids; Medicine; Peanut allergy; Decision analysis; Decision-making; Decision support system; Operations management; Alternative medicine; Allergy; Computer science; Data mining; Food allergy; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004453225,0.0002383328,0.0006805559,0.0001249201,0.0005541108,0.000006043991,0.0007017922,0.0003199803,0.0007454245],"category_scores_gemma":[0.001558445,0.000234077,0.00012884,0.0002003747,0.000260457,0.0001813117,0.0007804713,0.0004347232,0.00001242937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004030359,"about_ca_system_score_gemma":0.0005290078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001268254,"about_ca_topic_score_gemma":0.0004358453,"domain_scores_codex":[0.9965683,0.0007405739,0.001549734,0.0003987985,0.0002190539,0.0005235482],"domain_scores_gemma":[0.9951092,0.002278718,0.0008895007,0.0006913011,0.000940932,0.00009032297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008007474,0.0004942644,0.006014694,0.001042336,0.001710766,0.000002212094,0.2557861,0.00004137019,0.001559736,0.02130488,0.006405058,0.6976311],"study_design_scores_gemma":[0.001594266,0.0005612132,0.366009,0.0002748581,0.000001416187,0.000001077721,0.01674023,0.0001303944,0.0005663153,0.001903994,0.6119453,0.0002719385],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653034,0.01478583,0.001649008,0.01592912,0.0003558642,0.001339599,0.0001030943,0.00008241291,0.0004517131],"genre_scores_gemma":[0.9530755,0.001039446,0.04231397,0.003083787,0.00005895815,0.0003162455,0.00006391061,0.00003339077,0.00001476606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6973591,"threshold_uncertainty_score":0.9545381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2243841464337894,"score_gpt":0.4301453093651664,"score_spread":0.205761162931377,"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."}}