{"id":"W7147399370","doi":"10.1145/3769872.3769895","title":"Design and Evaluation of Visual Summaries to Improve Readability of Large Network Visualizations","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Readability; Visualization; Interpretability; Infographic; Data visualization; Interpretation (philosophy); Information visualization; Domain (mathematical analysis)","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":[0.0136447,0.001851209,0.001054805,0.002451272,0.0005317582,0.00319362,0.001928186,0.001214736,0.004999546],"category_scores_gemma":[0.1171298,0.000687452,0.0008636666,0.001308023,0.0006104698,0.004057277,0.002121371,0.001041185,0.0008171636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007530101,"about_ca_system_score_gemma":0.0008003787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000795761,"about_ca_topic_score_gemma":0.0007536759,"domain_scores_codex":[0.9917602,0.005420215,0.0009438019,0.0007692992,0.0008964391,0.0002100619],"domain_scores_gemma":[0.8798083,0.09113082,0.005621581,0.007190969,0.01384222,0.00240615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01586269,0.003678945,0.02139555,0.01636346,0.0007040093,0.001710297,0.04076472,0.04021331,0.1121512,0.006593833,0.01835841,0.7222037],"study_design_scores_gemma":[0.008899716,0.03203177,0.06616315,0.004460652,0.002656498,0.002253938,0.02228173,0.572247,0.1596182,0.02135514,0.1067534,0.001278821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7023024,0.001568694,0.2644875,0.0008399324,0.0003263965,0.004694438,0.001963713,0.02043269,0.00338423],"genre_scores_gemma":[0.5798734,0.0006707293,0.4112753,0.0002346271,0.00009868974,0.002904803,0.002096352,0.001132429,0.00171361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0136447,"threshold_uncertainty_score":0.0721609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03877080282877359,"score_gpt":0.3861728393101542,"score_spread":0.3474020364813806,"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."}}