{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.147635,0.002610789,0.002631462,0.004118992,0.01975561,0.03306452,0.00966697,0.04612834,0.01889451],"category_scores_gemma":[0.1119428,0.001528776,0.003694431,0.003042505,0.03397979,0.07772423,0.04207771,0.05914734,0.004962598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01193361,"about_ca_system_score_gemma":0.05556826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0053494,"about_ca_topic_score_gemma":0.007190217,"domain_scores_codex":[0.8650969,0.09085654,0.005207781,0.007481913,0.02052601,0.01083088],"domain_scores_gemma":[0.7250809,0.1713747,0.006042449,0.0135674,0.0305749,0.05335971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002728297,0.001778529,0.003343699,0.004020822,0.0001114937,0.001575888,0.09155662,0.001531478,0.00197384,0.1819843,0.3898555,0.321995],"study_design_scores_gemma":[0.0001110556,0.0002885794,0.001063604,0.005161691,0.0000428301,0.0007743966,0.1723998,0.001337554,0.0006372753,0.1911927,0.6267134,0.000277046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001704054,0.005145559,0.006734755,0.9803017,0.002706455,0.00009781648,0.00003590685,0.0002350195,0.003038798],"genre_scores_gemma":[0.1940719,0.03312699,0.2258127,0.5146251,0.007905405,0.003090027,0.0005293898,0.0009596964,0.0198788],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.147635,"threshold_uncertainty_score":0.7807776,"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."}}