{"id":"W2182833683","doi":"10.11575/prism/30809","title":"VisSTREAM: VISUALIZING TEMPORAL MULTIMEDIA CONVERSATIONS","year":2002,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Impromptu; Casual; Computer-supported cooperative work; Computer science; Multimedia; World Wide Web; Context (archaeology); Collaborative software; Interpersonal communication; Human–computer interaction; Work (physics); Communication; Psychology; Engineering","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":[0.0006179629,0.0007517039,0.0002865695,0.003225324,0.0005129803,0.002217506,0.0006757257,0.0009256878,0.01759641],"category_scores_gemma":[0.002231515,0.0003273233,0.0004523883,0.001598456,0.0003162303,0.001681246,0.00174709,0.0006052591,0.001813152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000389986,"about_ca_system_score_gemma":0.0007267846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005953783,"about_ca_topic_score_gemma":0.009623616,"domain_scores_codex":[0.999742,0.00006708614,0.00001840563,0.00004731011,0.00009249663,0.00003281945],"domain_scores_gemma":[0.9993336,0.0003226755,0.00007085773,0.00004949758,0.0001248701,0.00009856394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002699321,0.0003280218,0.01187307,0.002481942,0.0003195388,0.002167542,0.01043436,0.01982528,0.1100185,0.0211827,0.1631234,0.6555464],"study_design_scores_gemma":[0.0004894403,0.000431081,0.02923412,0.0009327793,0.0003251508,0.003444441,0.008751827,0.3535925,0.07093535,0.04863451,0.4828195,0.0004092233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1416335,0.005733575,0.6976947,0.001680632,0.0007163956,0.0006191588,0.03541701,0.0739211,0.042584],"genre_scores_gemma":[0.5429112,0.003503169,0.41249,0.0003220302,0.0002651789,0.0006017008,0.01737449,0.004715413,0.01781691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01759641,"threshold_uncertainty_score":0.05886579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1568175020156759,"score_gpt":0.3386676091790418,"score_spread":0.1818501071633659,"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."}}