{"id":"W2953949249","doi":"10.22260/isarc2019/0044","title":"Automatic Classification of Design Conflicts Using Rule-based Reasoning and Machine LearningAn Example of Structural Clashes Against the MEP Model","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Computer science; Machine learning; Artificial intelligence; Process (computing); Software; Task (project management); Software engineering; World Wide Web; Operating system; Systems engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002758222,0.001211267,0.0009532614,0.003804377,0.0009686097,0.001989541,0.00173621,0.001686979,0.003987534],"category_scores_gemma":[0.01151814,0.0004533201,0.001107538,0.002001781,0.001025488,0.001394493,0.001167766,0.00121034,0.0009461214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093811,"about_ca_system_score_gemma":0.001367223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004894589,"about_ca_topic_score_gemma":0.006236413,"domain_scores_codex":[0.9956052,0.0008037922,0.0004019511,0.0007109658,0.002242846,0.0002353068],"domain_scores_gemma":[0.9868016,0.007562325,0.001412975,0.001581195,0.002367827,0.0002741436],"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":[0.001357546,0.0007824028,0.04924646,0.0008886774,0.0002222333,0.005040852,0.002567843,0.1036796,0.05748239,0.01080689,0.01303913,0.7548862],"study_design_scores_gemma":[0.00005127097,0.0001788818,0.009094114,0.0001843956,0.00007984669,0.0009898373,0.0006975106,0.941526,0.02904905,0.008974665,0.009105668,0.00006885723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3611667,0.0009502235,0.614892,0.001090867,0.0002069472,0.0006090502,0.001549254,0.00946042,0.01007449],"genre_scores_gemma":[0.527392,0.0002031309,0.4676711,0.0001348627,0.00002816603,0.0001267237,0.001897333,0.0002231888,0.002323479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004894589,"threshold_uncertainty_score":0.01458704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04445482018926536,"score_gpt":0.2236294923329807,"score_spread":0.1791746721437154,"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."}}