{"id":"W4402933813","doi":"10.1177/10711813241280938","title":"Public Health Decision-Making Using Uncertainty Displays","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Public health; Computer science; Medicine; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008557521,0.001456573,0.0006560173,0.001678147,0.001028153,0.005586329,0.001318525,0.001544099,0.01704546],"category_scores_gemma":[0.05643001,0.0005222213,0.0009861388,0.001030067,0.0007946751,0.004796034,0.003963736,0.001106731,0.001222606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008808908,"about_ca_system_score_gemma":0.0009940919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001669538,"about_ca_topic_score_gemma":0.001621129,"domain_scores_codex":[0.9944225,0.004050023,0.0002662761,0.0004266013,0.000642458,0.0001920836],"domain_scores_gemma":[0.9419979,0.05263195,0.001361928,0.00178201,0.001580928,0.000645354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007408767,0.001278028,0.03756717,0.005546209,0.0005612469,0.002465721,0.08671132,0.08260456,0.02856673,0.05668242,0.05576161,0.6348463],"study_design_scores_gemma":[0.00217036,0.002648183,0.03892689,0.004799338,0.0009182909,0.001310715,0.04390107,0.4285801,0.03399826,0.1854667,0.2560958,0.001184227],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5011628,0.001421582,0.4163168,0.007958141,0.0004995182,0.001248977,0.004605351,0.01548919,0.05129759],"genre_scores_gemma":[0.8334895,0.0005945338,0.1612228,0.0003877725,0.00009756408,0.0006729248,0.0009283227,0.000378235,0.002228232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01704546,"threshold_uncertainty_score":0.05702275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05108678732153848,"score_gpt":0.3121209008720534,"score_spread":0.2610341135505149,"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."}}