{"id":"W106986401","doi":"","title":"Conceptualizing unexpected events in IT projects","year":2013,"lang":"en","type":"article","venue":"International Conference on Information Systems","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Scope (computer science); Unexpected events; Premise; Knowledge management; Computer science; Event (particle physics); Project management; Lead (geology); Process management; Data science; Risk analysis (engineering); Business; Engineering; Epistemology; Systems 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002249216,0.0001002751,0.00009836941,0.0002801256,0.00002772257,0.0003531486,0.0006379331,0.00005768019,0.00007144771],"category_scores_gemma":[0.0001473549,0.00009192833,0.00002165078,0.0002038259,0.000008526576,0.004027093,0.00007662814,0.0001307932,0.0005131065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009793007,"about_ca_system_score_gemma":0.00005505739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004545008,"about_ca_topic_score_gemma":0.000002973562,"domain_scores_codex":[0.998961,0.00004475293,0.0003861257,0.0001150793,0.0003607043,0.0001323937],"domain_scores_gemma":[0.9991437,0.00009491221,0.0001980657,0.0002043862,0.000319929,0.00003898177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007352422,0.00003324801,0.00228089,0.00002932242,0.00002278599,0.000001805295,0.004948518,0.001815081,0.0001183167,0.979926,0.004117166,0.006699481],"study_design_scores_gemma":[0.000665395,0.0001149057,0.007219044,0.0004732129,0.000001318959,0.00003406379,0.001893163,0.9433139,0.0003245536,0.002248903,0.04331164,0.0003998917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03073141,0.00001769359,0.8604159,0.003310152,0.003030698,0.001095162,0.000007996232,0.0008469542,0.100544],"genre_scores_gemma":[0.996624,0.00001092682,0.002635568,0.0002989068,0.00003390634,0.0002257841,0.00001604928,0.000003012808,0.0001518694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9776771,"threshold_uncertainty_score":0.6595117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05693561009443542,"score_gpt":0.3040020480898417,"score_spread":0.2470664379954063,"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."}}