{"id":"W3203764532","doi":"10.1177/14738716211045354","title":"Which emphasis technique to use? Perception of emphasis techniques with varying distractors, backgrounds, and visualization types","year":2021,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Emphasis (telecommunications); Computer science; Visualization; Perception; Predictability; Visual perception; Human–computer interaction; Data science; Artificial intelligence; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003466922,0.0002063558,0.0002336503,0.0004856006,0.0001754918,0.0006886426,0.0002370513,0.0001360245,0.00004348687],"category_scores_gemma":[0.000294649,0.0002006262,0.0000327223,0.002296432,0.00003426291,0.007601132,0.0001568199,0.00006338416,0.000014126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008798007,"about_ca_system_score_gemma":0.0001533376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005396992,"about_ca_topic_score_gemma":0.00002928598,"domain_scores_codex":[0.9982486,0.0001137815,0.0006568835,0.0002832593,0.0005065105,0.0001909404],"domain_scores_gemma":[0.9976522,0.00006221869,0.0003645994,0.000405805,0.001399603,0.0001155333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000160832,0.0009001999,0.04933305,0.001431817,0.0002469658,0.000007756204,0.02090087,0.002126653,0.05333201,0.6987799,0.003917387,0.1688625],"study_design_scores_gemma":[0.002415119,0.001431867,0.05875685,0.001772453,0.0002718345,0.0003433686,0.003113638,0.3978966,0.433631,0.001680252,0.0957692,0.00291777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01139515,0.000008160513,0.9869213,0.0001589926,0.0000644663,0.0003901248,0.00003671029,0.0003154159,0.0007096786],"genre_scores_gemma":[0.9392939,0.0001574808,0.05835681,0.0006382779,0.00002977094,0.00005210288,0.001380544,0.00002136315,0.00006976373],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9285645,"threshold_uncertainty_score":0.8181298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854502352333071,"score_gpt":0.3057490524211677,"score_spread":0.287204028897837,"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."}}