{"id":"W2059883798","doi":"10.1080/15427951.2011.604289","title":"NAViGaTOR: Large Scalable and Interactive Navigation and Analysis of Large Graphs","year":2011,"lang":"en","type":"article","venue":"Internet Mathematics","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Visualization; Computer science; Workflow; Graph drawing; Scalability; Graphical user interface; Data visualization; Graph Layout; Variety (cybernetics); Memory footprint; Interactive visualization; Data mining; Database; Programming language; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002251652,0.0001353051,0.0003819211,0.0001809188,0.00002808465,0.00002714673,0.0001127456,0.00003216607,0.0005161034],"category_scores_gemma":[0.000005423367,0.0001220871,0.0001299553,0.000351574,0.00005280663,0.000121743,0.0001527772,0.0001033776,0.000003839695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008865471,"about_ca_system_score_gemma":0.000004821706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001654806,"about_ca_topic_score_gemma":0.00002208029,"domain_scores_codex":[0.9991878,0.00002942195,0.0003350056,0.0001837075,0.0001052656,0.0001587637],"domain_scores_gemma":[0.9993121,0.00007658362,0.0002535758,0.0002216436,0.00008243015,0.00005364184],"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":[0.00002609745,0.001439999,0.4387688,0.0001344472,0.005403196,0.000002916001,0.02267537,0.000001684058,0.0005171234,0.5261449,0.001194018,0.003691477],"study_design_scores_gemma":[0.001592311,0.000434902,0.04500354,0.001050907,0.009147755,0.000008741807,0.009794952,0.5065194,0.04246745,0.3801103,0.002603068,0.001266689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914179,0.00004770668,0.1047129,0.000003656193,0.0000134286,0.0001026786,0.00005859213,0.00003017194,0.003612884],"genre_scores_gemma":[0.9908721,0.00000419238,0.008845278,0.00001008907,0.0000107788,0.00001313701,0.0000585378,0.00001234552,0.0001735285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5065177,"threshold_uncertainty_score":0.5650971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488171552979747,"score_gpt":0.2781225979841873,"score_spread":0.2632408824543898,"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."}}