{"id":"W2331503992","doi":"10.1177/154193120605001009","title":"Effects of Visualization Tools on Cardiac Telephone Consultation Processes","year":2006,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Waterloo","funders":"Ontario Ministry of Health and Long-Term Care; Family Process Institute; University of Ottawa","keywords":"Visualization; Information visualization; Computer science; Human–computer interaction; Data visualization; Interface (matter); Decision support system; Fidelity; Creative visualization; Domain (mathematical analysis); Data science; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002266908,0.0001515693,0.0002471369,0.00004330383,0.0002749054,0.0000469837,0.0001184737,0.0001131465,0.00001773853],"category_scores_gemma":[0.0002216386,0.0001194064,0.0001404529,0.0001645985,0.0001237982,0.0002329376,0.000041934,0.0001178658,0.000002007074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004113713,"about_ca_system_score_gemma":0.00001592764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001024775,"about_ca_topic_score_gemma":0.000002805296,"domain_scores_codex":[0.9990676,0.0000169943,0.0004207302,0.0002101663,0.0001342027,0.0001502864],"domain_scores_gemma":[0.998659,0.0002992548,0.0005884182,0.0000525843,0.0003736276,0.00002718178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005785135,0.001383891,0.2275376,0.005037535,0.0008407759,2.060287e-7,0.2600518,0.0002809643,0.3011307,0.1643817,0.03585855,0.002917644],"study_design_scores_gemma":[0.001494456,0.000267046,0.7037667,0.0005511687,0.0001492399,0.000001517588,0.02937802,0.0001188997,0.2600126,0.0008435448,0.002978622,0.0004381736],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955732,0.00009262567,0.00001301733,0.00002859131,0.0002827503,0.0002968848,0.00003337703,0.00004678747,0.003632778],"genre_scores_gemma":[0.9992546,0.00002593397,0.0000702919,0.00003884191,0.0001111879,0.00001924135,0.00001306011,0.00001844287,0.0004483858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4762291,"threshold_uncertainty_score":0.4869252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285363044527474,"score_gpt":0.2816307696208132,"score_spread":0.2687771391755384,"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."}}