{"id":"W2565859981","doi":"10.1109/cbi.2016.14","title":"Exploring Context Sensing in the Goal-Driven Design of Business Processes","year":2016,"lang":"en","type":"article","venue":"","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artifact-centric business process model; Business process modeling; Business process discovery; Business process; Context (archaeology); Process (computing); Process management; Business domain; Context model; Domain (mathematical analysis); Business Process Model and Notation; Business rule; Business process management; Business information; Knowledge management; Data science; Work in process; Business; Marketing; Artificial intelligence","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":[0.005669096,0.0009653796,0.0005238625,0.001161975,0.001279827,0.004141771,0.001612377,0.001532909,0.001229928],"category_scores_gemma":[0.007557516,0.001236028,0.001226307,0.0008888525,0.003348806,0.003957639,0.002985225,0.001998763,0.0002469115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00190271,"about_ca_system_score_gemma":0.003173526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0043816,"about_ca_topic_score_gemma":0.005916432,"domain_scores_codex":[0.996051,0.002244353,0.0002125782,0.0003921385,0.0008323638,0.0002676715],"domain_scores_gemma":[0.9963263,0.002448916,0.0003319849,0.0003273204,0.0003886478,0.0001769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000129512,0.0001730118,0.002087544,0.000593923,0.0001137568,0.0006359034,0.004572252,0.4294562,0.009331071,0.4828165,0.000611317,0.06947906],"study_design_scores_gemma":[0.00005584408,0.0001315842,0.0004660235,0.0002642794,0.00008739913,0.0001772893,0.001238253,0.6259469,0.007905007,0.3388273,0.02483081,0.00006932314],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01525882,0.0003619757,0.9783208,0.0006460377,0.00002406519,0.0001117857,0.00001792473,0.0001014126,0.00515715],"genre_scores_gemma":[0.4592511,0.0007231054,0.5381188,0.0001771106,0.00002062598,0.0002723504,0.00006060608,0.00007214193,0.001304214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005669096,"threshold_uncertainty_score":0.02998143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335866394856672,"score_gpt":0.2343678838651199,"score_spread":0.1007812443794526,"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."}}