{"id":"W3207535187","doi":"10.1109/mcg.2021.3112845","title":"Communicating Patient Health Data: A Wicked Problem","year":2021,"lang":"en","type":"preprint","venue":"IEEE Computer Graphics and Applications","topic":"Persona Design and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Calgary; University of Victoria; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Health care; Action (physics); Exploratory research; Process (computing); Space (punctuation); Data science; Work (physics); Data visualization; Patient data; Call to action; Human–computer interaction; Internet privacy; Artificial intelligence; Engineering; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004612185,0.0003774608,0.0004897214,0.0001826719,0.0007756664,0.000887068,0.003781547,0.000198976,0.00000117221],"category_scores_gemma":[0.000002580841,0.0004042176,0.0001154418,0.0006312664,0.0002316456,0.0002659599,0.005758412,0.0009127725,0.000007397189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004693152,"about_ca_system_score_gemma":0.0004911323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002426905,"about_ca_topic_score_gemma":0.00008527542,"domain_scores_codex":[0.9968771,0.0001886327,0.0006870555,0.001506941,0.0003320606,0.0004082079],"domain_scores_gemma":[0.9934627,0.000179613,0.0005381247,0.00529189,0.00022603,0.0003015783],"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":[0.000001331925,0.0008222858,0.00008310179,0.0004663558,0.0002022113,0.000004504437,0.004475715,0.0003564068,0.0001212427,0.5633094,0.01519654,0.414961],"study_design_scores_gemma":[0.0003592703,0.00008438814,0.0004052875,0.0004115034,0.00004408669,0.00007122611,0.0001439726,0.7932714,0.00004512077,0.03474839,0.1693487,0.001066581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001181075,0.003595433,0.9870393,0.005865011,0.0001526349,0.001460729,0.0001716702,0.0003574359,0.0001766812],"genre_scores_gemma":[0.2147633,0.00410691,0.7720653,0.005012872,0.0003947896,0.002143562,0.001441303,0.00005218617,0.00001976728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.792915,"threshold_uncertainty_score":0.999841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06862120949665804,"score_gpt":0.3046611163745018,"score_spread":0.2360399068778438,"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."}}