{"id":"W1537892751","doi":"10.1111/cgf.12644","title":"Detangler: Visual Analytics for Multiplex Networks","year":2015,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Multiplex; Cohesion (chemistry); Visual analytics; Feature (linguistics); Network analysis; Human–computer interaction; Data mining; Visualization; Distributed computing; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004469897,0.0002294931,0.0002661943,0.0002750464,0.0001736605,0.0004278038,0.001143503,0.0001263912,0.000001727011],"category_scores_gemma":[0.00004966332,0.0002212426,0.0001859031,0.0009717687,0.00007629038,0.0005282403,0.0005416624,0.000140498,0.00001792592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003244732,"about_ca_system_score_gemma":0.00009502394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005187906,"about_ca_topic_score_gemma":0.0000276155,"domain_scores_codex":[0.9982008,0.00005131374,0.0003815806,0.0004883739,0.0003427361,0.00053519],"domain_scores_gemma":[0.9983095,0.0001284163,0.0001482791,0.0006305181,0.0004265103,0.0003567785],"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":[0.00001157966,0.000200552,0.005058608,0.00001614445,0.0000873018,0.00001043523,0.0001624176,0.009308158,0.000002059008,0.8655214,0.1020617,0.01755971],"study_design_scores_gemma":[0.0007714732,0.0002071225,0.0001799365,0.00001260501,0.0000157675,0.000008207019,0.00002086644,0.918721,0.00002096764,0.007298748,0.07247073,0.0002725295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002874123,0.0001151253,0.9969936,0.0006898813,0.001240363,0.0002398025,0.00001226456,0.0003072962,0.0001142335],"genre_scores_gemma":[0.6914315,0.00008080444,0.2940627,0.01238182,0.001149532,0.00004113768,0.0003828828,0.00008019902,0.0003894191],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9094129,"threshold_uncertainty_score":0.9022013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04452672229331042,"score_gpt":0.3066135240822644,"score_spread":0.262086801788954,"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."}}