{"id":"W4388458609","doi":"10.18280/isi.280513","title":"Enhancing Robotic Process Automation Task Selection: An Integrated Approach Leveraging Process Mining and Feature Extraction","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Robotic Process Automation Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automation; Process (computing); Computer science; Task (project management); Process mining; Selection (genetic algorithm); Artificial intelligence; Feature selection; Feature extraction; Process automation system; Work in process; Engineering; Systems engineering; Business process modeling; Operations management; Business process","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003056173,0.001514762,0.001306765,0.005501823,0.0007170758,0.002361755,0.001116435,0.0007850021,0.00121041],"category_scores_gemma":[0.008965592,0.0005154012,0.001388971,0.003149146,0.0004520766,0.002073362,0.001876179,0.0009923403,0.000642192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007501545,"about_ca_system_score_gemma":0.003000549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003909323,"about_ca_topic_score_gemma":0.006286907,"domain_scores_codex":[0.9970449,0.0007498258,0.0002685318,0.0004988838,0.00119086,0.0002471333],"domain_scores_gemma":[0.9940842,0.002610635,0.001022104,0.0004894618,0.001619773,0.0001738165],"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":[0.0002744865,0.001115864,0.01722179,0.0006013828,0.0002214956,0.0002274315,0.0005495024,0.07438131,0.02882034,0.003064054,0.00242985,0.8710924],"study_design_scores_gemma":[0.00006631239,0.0007983989,0.01811403,0.0001148166,0.0002078294,0.0002990854,0.0006775258,0.9313419,0.02610212,0.01400536,0.008142919,0.000129685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04392788,0.0002978846,0.9519159,0.0002808036,0.00002142177,0.0004222584,0.0002593529,0.001295302,0.00157928],"genre_scores_gemma":[0.2807623,0.0002513242,0.7165357,0.00007506149,0.00004107268,0.0003301767,0.0008313606,0.0001013411,0.001071663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005501823,"threshold_uncertainty_score":0.01616275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291398064982771,"score_gpt":0.2491760765471074,"score_spread":0.2362620958972797,"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."}}