{"id":"W2084367598","doi":"10.1145/2554850.2555076","title":"Big data meets process mining","year":2014,"lang":"en","type":"article","venue":"","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Scalability; Computer science; Process mining; Process (computing); Distributed computing; Big data; Data mining; Event (particle physics); Computation; Business process discovery; Distributed Computing Environment; Distributed database; Work in process; Database; Business process; Business process management; Business process modeling; Algorithm; 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":[0.009398572,0.002135971,0.002802722,0.003828566,0.002115736,0.01176935,0.003173294,0.004169712,0.01309368],"category_scores_gemma":[0.04307186,0.001698426,0.002607023,0.007387651,0.004224312,0.02059271,0.008608329,0.006181854,0.01212321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001917565,"about_ca_system_score_gemma":0.005218969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002040049,"about_ca_topic_score_gemma":0.001373298,"domain_scores_codex":[0.9791033,0.004337935,0.001833793,0.004267622,0.009724207,0.0007331707],"domain_scores_gemma":[0.9654623,0.01497645,0.001917911,0.01108865,0.004929941,0.001624744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003288831,0.0001809419,0.004548785,0.001952506,0.000312851,0.0007218422,0.0005432941,0.01095315,0.002902115,0.6149532,0.05399881,0.3086036],"study_design_scores_gemma":[0.00006805855,0.00006421532,0.0008453259,0.0002411843,0.00005981189,0.0005895852,0.0003464884,0.0464284,0.002602178,0.7681158,0.1805818,0.00005716949],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.003991778,0.006461515,0.9029701,0.02627813,0.00161361,0.0005742657,0.003058125,0.004412464,0.05063993],"genre_scores_gemma":[0.1435241,0.008290919,0.8156374,0.006715228,0.004419801,0.001116568,0.007475135,0.001418543,0.01140236],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01309368,"threshold_uncertainty_score":0.04970497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08435997427120145,"score_gpt":0.2642391584540387,"score_spread":0.1798791841828372,"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."}}