{"id":"W2148893894","doi":"10.1111/cgf.12378","title":"ConVis: A Visual Text Analytic System for Exploring Blog Conversations","year":2014,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Automatic summarization; Metadata; Visualization; Set (abstract data type); Domain (mathematical analysis); Information retrieval; World Wide Web; Information visualization; Visual analytics; Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002417456,0.001420676,0.0005622587,0.003527405,0.000852001,0.002659063,0.001670497,0.0008603566,0.01974113],"category_scores_gemma":[0.007785007,0.0004990877,0.00055188,0.001579283,0.0005728907,0.002242932,0.003253587,0.00118897,0.003125353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005150128,"about_ca_system_score_gemma":0.0007895409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001598689,"about_ca_topic_score_gemma":0.001877718,"domain_scores_codex":[0.9992034,0.0002760855,0.00006016225,0.0001374144,0.0002775265,0.00004542203],"domain_scores_gemma":[0.9948032,0.003155307,0.0003329322,0.0005836081,0.000772253,0.0003527233],"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":[0.003101315,0.0004654917,0.006115937,0.002290743,0.0002268266,0.001139167,0.01226111,0.008363128,0.1265654,0.0207224,0.1609146,0.6578339],"study_design_scores_gemma":[0.0009359503,0.000853889,0.0101647,0.0009991556,0.0002281397,0.001688796,0.005472914,0.4500804,0.125415,0.05509394,0.3485459,0.0005210684],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03262057,0.0004455292,0.8160119,0.0008233814,0.0001764365,0.000692211,0.006050838,0.134882,0.008297155],"genre_scores_gemma":[0.2244897,0.0004751082,0.7521479,0.0003501688,0.0001887872,0.001612333,0.005809875,0.007760431,0.007165827],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01974113,"threshold_uncertainty_score":0.06604069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03715807506847913,"score_gpt":0.2763169287340402,"score_spread":0.2391588536655611,"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."}}