{"id":"W2158943277","doi":"10.1109/tvcg.2008.175","title":"VisGets: Coordinated Visualizations for Web-based Information Exploration and Discovery","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Information retrieval; Web navigation; World Wide Web; RSS; Filter (signal processing); Exploratory search; Web search query; Visualization; Web page; Data visualization; Dimension (graph theory); Search engine; Data mining","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":[0.0001644853,0.0001875702,0.0001847845,0.0006240438,0.0007374207,0.0003983521,0.000167295,0.0000964278,0.000001879258],"category_scores_gemma":[0.000007522107,0.0001885577,0.00007468004,0.0009604464,0.00009435444,0.003066045,0.000004919257,0.00008117559,0.000002804671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001726563,"about_ca_system_score_gemma":0.0000763307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001265579,"about_ca_topic_score_gemma":0.00001152764,"domain_scores_codex":[0.9988745,0.00008211649,0.0003493518,0.000313157,0.0002104412,0.000170365],"domain_scores_gemma":[0.9991466,0.0001342081,0.0001303764,0.0002566809,0.0002354144,0.00009667095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009343941,0.000696774,0.0004547606,0.0002062915,0.0002033329,0.000003693342,0.004087307,0.01762727,0.000122022,0.9425414,0.002849618,0.03111406],"study_design_scores_gemma":[0.0009829935,0.0002377196,0.0002228577,0.00003417109,0.00003266855,0.000008900302,0.00003769128,0.9947575,0.0008262391,0.0003655516,0.002265791,0.0002278818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006522303,0.00001877434,0.9924024,0.0002154116,0.0002543762,0.0002478144,0.00005789291,0.0002695887,0.00001142226],"genre_scores_gemma":[0.9931772,0.0002900785,0.004908117,0.001292768,0.0000306066,0.00007793954,0.0001770545,0.00001340691,0.00003278214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9874943,"threshold_uncertainty_score":0.7689161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02577688320399458,"score_gpt":0.2634437113893258,"score_spread":0.2376668281853312,"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."}}