{"id":"W2998073349","doi":"10.1109/vahc47919.2019.8945039","title":"PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"European Commission; Strategiske Forskningsråd","keywords":"Computer science; Padé approximant; Human–computer interaction; Visualization; Computer graphics (images); Artificial intelligence; Mathematics","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":[0.0003888596,0.0001689035,0.0004972078,0.0002543587,0.00007051029,0.0002537529,0.0009235577,0.00004636175,0.0000417669],"category_scores_gemma":[0.00004081204,0.0001182003,0.00005424938,0.0031143,0.00002791375,0.0008049888,0.0004888161,0.00006234199,0.00002631313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004438207,"about_ca_system_score_gemma":0.0002773897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006608926,"about_ca_topic_score_gemma":0.00009274288,"domain_scores_codex":[0.9978223,0.0001510081,0.0005955044,0.0005858256,0.0005806462,0.00026471],"domain_scores_gemma":[0.9975919,0.0001248918,0.0005921213,0.001159652,0.0004200338,0.0001113749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005490243,0.0006934259,0.09355172,0.0004358521,0.003909583,0.00005012277,0.005408701,0.003136629,0.0001613218,0.8900309,0.002150211,0.0004166113],"study_design_scores_gemma":[0.0003147244,0.0003517705,0.0006616223,0.00007478647,0.0002781682,0.000002916643,0.01375208,0.9827067,0.000302579,0.000001023792,0.001361706,0.0001919594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1082409,0.00003429176,0.8849816,0.00006865446,0.00019177,0.0006355757,0.001283588,0.0001460832,0.00441759],"genre_scores_gemma":[0.9964305,0.000001885438,0.002314337,0.00006465316,0.00001012671,0.000007385846,0.0007795281,0.000007661334,0.0003839561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.97957,"threshold_uncertainty_score":0.482007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210311037787432,"score_gpt":0.3392476650014512,"score_spread":0.318216561222708,"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."}}