{"id":"W4386252546","doi":"10.31219/osf.io/7fdb5","title":"Educational Data Comics: What can Comics do for Education in Visualization?","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Austrian Science Fund","keywords":"Comics; Visualization; Computer science; Information visualization; Data visualization; World Wide Web; Data science; Subject (documents); Multimedia; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01694379,0.001275552,0.0009022145,0.004084016,0.002688967,0.01604951,0.002149283,0.004822922,0.02553484],"category_scores_gemma":[0.05383411,0.0005730964,0.0008579898,0.004453318,0.006628944,0.03617633,0.007625644,0.004649234,0.006849475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0034723,"about_ca_system_score_gemma":0.004135193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002572363,"about_ca_topic_score_gemma":0.002602377,"domain_scores_codex":[0.9918447,0.005539083,0.0003694401,0.0005331049,0.001057515,0.0006560749],"domain_scores_gemma":[0.947611,0.03517228,0.002345649,0.005838534,0.006043721,0.002988811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001930899,0.0003501122,0.007802856,0.003768922,0.00004264958,0.0002956803,0.02057296,0.001041891,0.00128273,0.3272512,0.08776823,0.5496297],"study_design_scores_gemma":[0.00005335117,0.0001440233,0.002588947,0.00649656,0.00003980224,0.000327806,0.02238465,0.001772494,0.002158798,0.202092,0.7618743,0.00006731445],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.04011514,0.07223676,0.2025194,0.5357006,0.005339091,0.0004154487,0.001085425,0.004497058,0.1380911],"genre_scores_gemma":[0.57781,0.08564781,0.2490949,0.03684615,0.003761902,0.001158318,0.002107723,0.001749101,0.04182407],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02553484,"threshold_uncertainty_score":0.08960843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1027133357837961,"score_gpt":0.4238256684920536,"score_spread":0.3211123327082575,"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."}}