{"id":"W2105893525","doi":"10.1109/tvcg.2007.70521","title":"VisLink: Revealing Relationships Amongst Visualizations","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Pennsylvania","keywords":"Computer science; Visualization; Bridging (networking); Data visualization; Reuse; Human–computer interaction; Variety (cybernetics); Information visualization; Encoding (memory); Space (punctuation); Theoretical computer science; Information retrieval; Data mining; Artificial intelligence","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":[0.001802577,0.00144148,0.0007440531,0.004062734,0.00140305,0.005951791,0.001504664,0.001279966,0.01515759],"category_scores_gemma":[0.01100284,0.0007734778,0.0008810993,0.003014677,0.0008784458,0.006547768,0.006593753,0.001672128,0.003013584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005381605,"about_ca_system_score_gemma":0.001053421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001957382,"about_ca_topic_score_gemma":0.003151003,"domain_scores_codex":[0.9984826,0.0004973006,0.00007347548,0.000314266,0.0005156103,0.0001167783],"domain_scores_gemma":[0.9951101,0.002669914,0.0004547188,0.0008822876,0.0005779946,0.0003050593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000970901,0.0002281818,0.00512269,0.001623158,0.0002217912,0.0009153788,0.007597636,0.0121649,0.0559308,0.09691773,0.05485085,0.7634559],"study_design_scores_gemma":[0.000286865,0.0003820107,0.005548963,0.0005772323,0.0002464834,0.001936285,0.004365622,0.315652,0.09296396,0.2654727,0.3122244,0.0003436128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02361185,0.0007416125,0.9463956,0.0005600607,0.0001411496,0.0001941314,0.001686081,0.02058155,0.006088],"genre_scores_gemma":[0.1475051,0.0007731976,0.8386001,0.0002209315,0.0001014321,0.0003565207,0.002940208,0.00334393,0.00615869],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01515759,"threshold_uncertainty_score":0.05070716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03493980262763771,"score_gpt":0.3009453598490365,"score_spread":0.2660055572213988,"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."}}