{"id":"W2783562028","doi":"","title":"Designing user engagement for cognitively-enhanced processes","year":2017,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Process (computing); Business process management; Business process; Process management; Analytics; Human–computer interaction; Knowledge management; Usability; Automation; Cognition; Data science; Work in process; 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":[0.01158938,0.00126543,0.0005995164,0.001051201,0.001559009,0.004200384,0.001864582,0.00221445,0.005171827],"category_scores_gemma":[0.03755032,0.0009980666,0.0008745922,0.0006008762,0.002151671,0.006206599,0.005124091,0.001543995,0.001082275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001472289,"about_ca_system_score_gemma":0.00174871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008077229,"about_ca_topic_score_gemma":0.001065415,"domain_scores_codex":[0.9841117,0.01241799,0.0005063249,0.001092044,0.001247421,0.0006245865],"domain_scores_gemma":[0.9772889,0.01603635,0.0008864736,0.003385394,0.001636519,0.0007664604],"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":[0.001834939,0.00373224,0.03520574,0.002772738,0.0002759132,0.001524491,0.1364824,0.04851729,0.1157663,0.2628064,0.004023124,0.3870585],"study_design_scores_gemma":[0.0009626269,0.003685361,0.008823067,0.001062857,0.0004887232,0.001236767,0.02747087,0.6056319,0.07223763,0.1714953,0.1065805,0.0003244007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1230856,0.0000883243,0.8635311,0.000655635,0.00002452439,0.0007259441,0.00003876436,0.001119371,0.01073065],"genre_scores_gemma":[0.6944401,0.00008407421,0.3018506,0.000149186,0.000009225158,0.001360544,0.00008537164,0.0001301414,0.001890869],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01158938,"threshold_uncertainty_score":0.06129122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02943943021713029,"score_gpt":0.2409766898395647,"score_spread":0.2115372596224344,"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."}}