{"id":"W2414963195","doi":"10.1007/s10111-016-0374-2","title":"Incident response teams in IT operations centers: the T-TOCs model of team functionality","year":2016,"lang":"en","type":"article","venue":"Cognition Technology & Work","topic":"Information Systems Theories and Implementation","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Incident response; Parallels; Context (archaeology); Incident report; Work (physics); Ethnography; Knowledge management; Position (finance); Computer science; Psychology; Operations management; Engineering; Computer security; Business; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002200706,0.0004121975,0.0003696627,0.002161921,0.001553473,0.005147214,0.002371334,0.002043269,0.01274227],"category_scores_gemma":[0.009898409,0.0005416684,0.001114905,0.001617423,0.004255852,0.008149782,0.002681306,0.001278638,0.001751071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002063462,"about_ca_system_score_gemma":0.004273204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01235741,"about_ca_topic_score_gemma":0.005228236,"domain_scores_codex":[0.9972983,0.001538369,0.0001444061,0.0003230984,0.0003211841,0.0003746124],"domain_scores_gemma":[0.9928866,0.003371554,0.0008299006,0.0009198979,0.001176201,0.0008158623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002307202,0.0002954353,0.01475592,0.000151419,0.00007071167,0.0003813145,0.008606996,0.04327983,0.001590232,0.8956646,0.002878187,0.03209463],"study_design_scores_gemma":[0.0002185943,0.0003860258,0.009016425,0.0001579129,0.0001288018,0.0003994099,0.01023233,0.4962983,0.000688281,0.4746727,0.007736832,0.00006431936],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4241171,0.0001577303,0.4323666,0.006792415,0.00009301883,0.0003997115,0.0004493681,0.000566786,0.1350572],"genre_scores_gemma":[0.9805638,0.00003899699,0.01653088,0.00006187971,0.00001718842,0.0001019283,0.00006447569,0.00002556075,0.002595187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01274227,"threshold_uncertainty_score":0.04262716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03121216875937175,"score_gpt":0.324547765103586,"score_spread":0.2933355963442142,"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."}}