{"id":"W3200503446","doi":"","title":"Information Visualization for Systems People","year":2002,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Information visualization; Information system; Human–computer interaction; Artificial intelligence; 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":[0.002975644,0.002233173,0.00127472,0.003820567,0.001431082,0.008169185,0.001465512,0.00159571,0.1603505],"category_scores_gemma":[0.01017724,0.00139481,0.00125074,0.005147082,0.0006829327,0.008881133,0.004050098,0.003119259,0.06746854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114911,"about_ca_system_score_gemma":0.002142912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005764708,"about_ca_topic_score_gemma":0.00740246,"domain_scores_codex":[0.9987466,0.0003577351,0.0001171429,0.0002466352,0.000422798,0.0001090367],"domain_scores_gemma":[0.9941574,0.001273896,0.0002176149,0.002548974,0.001320334,0.0004816944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009342011,0.00005943197,0.0007041707,0.0003927223,0.00006083945,0.00009169895,0.0006023255,0.0008082582,0.002022063,0.03710978,0.6964882,0.2615671],"study_design_scores_gemma":[0.00005250091,0.00003710253,0.001227111,0.0002835412,0.00006493286,0.0001663003,0.000198466,0.0127341,0.002661817,0.073851,0.9086809,0.00004229846],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00435782,0.003099449,0.5709409,0.009186313,0.002128725,0.0004884902,0.03093789,0.2705771,0.1082832],"genre_scores_gemma":[0.06320029,0.005224194,0.6236784,0.002174155,0.001271018,0.001369546,0.06160158,0.05344722,0.1880335],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1603505,"threshold_uncertainty_score":0.5364259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0352360210263221,"score_gpt":0.2951441122454369,"score_spread":0.2599080912191148,"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."}}