{"id":"W4416072333","doi":"10.2312/eved.20251004","title":"From Reality to Recognition: Evaluating Visualization Analogies for Novice Chart Comprehension","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Visualization; Chart; Comprehension; Data visualization; Pie chart; Information visualization; Creative visualization","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006612902,0.0002975161,0.000418385,0.0002415759,0.0002334621,0.000321048,0.001068164,0.0002263499,0.00003937275],"category_scores_gemma":[0.0007614837,0.000318241,0.0001402521,0.0006034361,0.00003413425,0.0003051828,0.001787523,0.0002009932,0.0001114428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001058977,"about_ca_system_score_gemma":0.0002498748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002609432,"about_ca_topic_score_gemma":0.00006022408,"domain_scores_codex":[0.9974059,0.0002198826,0.000637754,0.001060708,0.0004031784,0.0002725144],"domain_scores_gemma":[0.997165,0.0003600197,0.0003580501,0.001120054,0.000879892,0.0001169344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000470918,0.00246626,0.09325841,0.005525806,0.001817423,0.00003786123,0.02129364,0.04566286,0.01175502,0.06327002,0.2627676,0.4916742],"study_design_scores_gemma":[0.0008962874,0.0001805114,0.02666051,0.001430226,0.0002007105,9.346995e-7,0.0002657512,0.9269083,0.004044393,0.01671367,0.02166241,0.00103625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06323676,0.00005712405,0.9311573,0.00198961,0.001232091,0.0007328046,0.0007468732,0.0004069719,0.0004404698],"genre_scores_gemma":[0.6536601,0.0004095113,0.2820001,0.0230151,0.002801081,0.0007360981,0.03496892,0.0001133482,0.002295832],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8812455,"threshold_uncertainty_score":0.999927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2597139608255297,"score_gpt":0.4423593463868498,"score_spread":0.18264538556132,"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."}}