{"id":"W4286611169","doi":"10.1145/3528223.3530111","title":"Perception of letter glyph parameters for InfoTypography","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Glyph (data visualization); Font; Computer science; Visualization; Range (aeronautics); Sentence; Typography; Perception; Natural language processing; Artificial intelligence; Interval (graph theory); Chinese characters; Information retrieval; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002025121,0.0005070799,0.0002613602,0.0009289436,0.0005653016,0.003913126,0.0003977753,0.0007540531,0.004792148],"category_scores_gemma":[0.04161565,0.0001915922,0.000280063,0.0005679858,0.000726092,0.002325254,0.001303182,0.0006062522,0.0008826854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006160617,"about_ca_system_score_gemma":0.0003102352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007271837,"about_ca_topic_score_gemma":0.000579869,"domain_scores_codex":[0.9981015,0.0009192604,0.0001737819,0.0002470035,0.0004751043,0.00008329179],"domain_scores_gemma":[0.9717411,0.01936438,0.002316697,0.002252658,0.003289874,0.001035197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.006403996,0.0003970793,0.1543964,0.002186451,0.0001970784,0.001392163,0.03888681,0.00961417,0.3531907,0.01827181,0.01189452,0.4031689],"study_design_scores_gemma":[0.0003776589,0.002774528,0.5914565,0.001723306,0.0004806972,0.005817536,0.05324662,0.0637016,0.1516383,0.03667637,0.09104838,0.00105855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337534,0.0006097581,0.03827481,0.0004069192,0.0001616122,0.0001558949,0.0004296782,0.0009876097,0.02522028],"genre_scores_gemma":[0.9855859,0.000110277,0.01281164,0.00007869735,0.00001701184,0.00005654488,0.0001851438,0.0002469922,0.0009078623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004792148,"threshold_uncertainty_score":0.01603132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03172951379207583,"score_gpt":0.2858545176409286,"score_spread":0.2541250038488528,"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."}}