{"id":"W4386249107","doi":"10.1167/jov.23.9.5504","title":"Psychophysics of variable fonts: Speed and comprehension measures","year":2023,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Words per minute; Comprehension; Reading (process); Reading comprehension; Set (abstract data type); Computer science; Stroke (engine); Variable (mathematics); Range (aeronautics); Psychology; Artificial intelligence; Cognitive psychology; Mathematics; Linguistics; Physics; Engineering","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":[0.0006645274,0.0006484172,0.0003465029,0.0003860901,0.0001832044,0.0007394715,0.0002656539,0.0005333758,0.003325782],"category_scores_gemma":[0.01017481,0.0002561788,0.000393464,0.0003138129,0.0003077243,0.0007259041,0.0004552519,0.000623774,0.0006213585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001274218,"about_ca_system_score_gemma":0.0000901584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002750991,"about_ca_topic_score_gemma":0.0002491349,"domain_scores_codex":[0.9993694,0.0001554733,0.0000925977,0.000174113,0.000172289,0.00003615573],"domain_scores_gemma":[0.9950632,0.002656644,0.0009090484,0.0005498455,0.0006041447,0.0002171975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00281742,0.0007142326,0.02009503,0.0006168463,0.0001285798,0.0002382206,0.00192778,0.001319465,0.9347495,0.0002388478,0.0006543156,0.03649972],"study_design_scores_gemma":[0.0003236887,0.00999786,0.7260303,0.00007730335,0.0002452683,0.001346661,0.0008920267,0.009061065,0.2466528,0.001397961,0.003790819,0.0001841609],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849572,0.0002104131,0.01168408,0.00003633299,0.00004364039,0.0002579235,0.0004768031,0.0002596036,0.002073973],"genre_scores_gemma":[0.9831843,0.0001359915,0.01381958,0.00009148617,0.00004201429,0.0006613857,0.0005289817,0.0001912231,0.001345161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003325782,"threshold_uncertainty_score":0.01112586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05995893238564853,"score_gpt":0.3413141208410084,"score_spread":0.2813551884553598,"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."}}