{"id":"W4415762104","doi":"10.1002/cjce.70032","title":"Transforming chemical process engineering: The role of <scp>AI</scp> and machine learning in revolutionizing process systems","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Transformative learning; Work in process; Industry 4.0; Process modeling; Artificial neural network; Expert system; Process safety","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003158755,0.0001599086,0.000248667,0.0002472642,0.00005253473,0.00006774612,0.0002656588,0.0001110534,0.000001484392],"category_scores_gemma":[0.0005579179,0.0001192888,0.00004773691,0.0005222548,0.00004337858,0.000206264,0.000006738322,0.0007628517,1.585221e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001640093,"about_ca_system_score_gemma":0.000200028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001651261,"about_ca_topic_score_gemma":0.00004502989,"domain_scores_codex":[0.9990347,0.000009367792,0.0004580555,0.00008397185,0.0001478178,0.0002660636],"domain_scores_gemma":[0.9994466,0.0001256035,0.00006782057,0.00007859815,0.0001487045,0.0001326408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002364996,0.00000340145,0.0004183383,0.0003615383,0.00003754062,0.000001905369,0.001156538,0.9434395,0.0529152,0.001211747,0.00001303379,0.0004388835],"study_design_scores_gemma":[0.0001946697,0.000006959303,0.00002429206,0.0005008611,0.00002305122,0.00004890264,0.0002302668,0.8195046,0.1785085,0.00009507022,0.0008029187,0.00005998538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591108,0.01654464,0.02255592,0.0003122458,0.0002685027,0.0003073752,0.000005749658,0.00008750748,0.0008072486],"genre_scores_gemma":[0.9997287,0.00003437889,0.0001155594,0.00001623958,0.00005685758,0.00001210125,0.000002523024,0.00002421439,0.000009404501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1255933,"threshold_uncertainty_score":0.4864455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004128082226165486,"score_gpt":0.1816624315399598,"score_spread":0.1775343493137943,"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."}}