{"id":"W2758669266","doi":"10.1109/re.2017.62","title":"ECrits — Visualizing Support Ticket Escalation Risk","year":2017,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Ticket; Process (computing); Task (project management); Customer intelligence; Decision support system; IBM; Product (mathematics)","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":[0.002310321,0.001638379,0.0006263565,0.007322678,0.0004486916,0.003448209,0.001247981,0.00131282,0.009674916],"category_scores_gemma":[0.01280234,0.0004126433,0.0008572371,0.003597581,0.0003847419,0.002800906,0.002201613,0.001233575,0.00201248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006853646,"about_ca_system_score_gemma":0.0009312534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008650898,"about_ca_topic_score_gemma":0.009859916,"domain_scores_codex":[0.9983753,0.000282123,0.0001683683,0.0002715662,0.0007733046,0.0001292708],"domain_scores_gemma":[0.9927545,0.003127978,0.0011316,0.001000968,0.001519334,0.0004655292],"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":[0.002262253,0.001000501,0.1351128,0.002156183,0.0006869576,0.002628858,0.008614625,0.1003957,0.0184774,0.01947141,0.2238183,0.4853752],"study_design_scores_gemma":[0.0002215542,0.0006062894,0.0787011,0.0005866727,0.0002400835,0.002012942,0.004406472,0.7548435,0.01845584,0.0213067,0.1182961,0.0003226679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4729342,0.004129153,0.2753265,0.003514926,0.0007375377,0.001039042,0.0757054,0.1193554,0.04725796],"genre_scores_gemma":[0.7758926,0.001175627,0.1757128,0.0002780147,0.0001305666,0.0003349824,0.03423157,0.003414651,0.008829203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009674916,"threshold_uncertainty_score":0.0323658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03021268026713663,"score_gpt":0.3306504797441246,"score_spread":0.300437799476988,"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."}}