{"id":"W4388469749","doi":"10.1109/tvcg.2023.3327378","title":"Challenges and Opportunities in Data Visualization Education: A Call to Action","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Visualization; Data visualization; Call to action; Action (physics); Data science; Information visualization; Geovisualization; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004451422,0.0002098284,0.0002016137,0.001307042,0.0002120333,0.0002963127,0.0004426993,0.0001092555,0.000004308338],"category_scores_gemma":[0.000009275648,0.0002296789,0.00002507356,0.001361592,0.00005256464,0.001042309,0.00004101796,0.0001106528,0.00001507563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002486616,"about_ca_system_score_gemma":0.0001141959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001869385,"about_ca_topic_score_gemma":0.0002351564,"domain_scores_codex":[0.9982321,0.0001687647,0.0003650519,0.0006861958,0.0003221144,0.0002257626],"domain_scores_gemma":[0.9988483,0.00009501406,0.00008271073,0.0006297385,0.0001454251,0.0001988438],"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":[0.000008192864,0.0002360482,0.0000279384,0.00008718256,0.00002008617,0.000003960107,0.002074763,0.000292934,0.000005957088,0.7843547,0.001935528,0.2109527],"study_design_scores_gemma":[0.0003267494,0.0001219973,0.001371241,0.0001159071,0.00001409457,0.00001566524,0.0003470749,0.9754877,0.00007707171,0.0009140372,0.02091713,0.0002912957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002199019,0.0001663807,0.9951171,0.001094116,0.0006531397,0.0002563898,0.00002441224,0.0003893448,0.0001001444],"genre_scores_gemma":[0.9394901,0.04751384,0.001914611,0.009200939,0.0002245595,0.0001103197,0.0005449503,0.00007836022,0.000922317],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9932024,"threshold_uncertainty_score":0.9366035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1894605379174595,"score_gpt":0.3791275389805828,"score_spread":0.1896670010631233,"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."}}