{"id":"W7081944215","doi":"10.1016/j.addma.2025.104941","title":"Real-time multivariable control of directed energy deposition via adaptive model predictive control","year":2025,"lang":"en","type":"article","venue":"Additive manufacturing","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multivariable calculus; Model predictive control; Deposition (geology); Thermal; Control theory (sociology); Process control; Adaptive control; Energy (signal processing); Process (computing)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000172302,0.0002423849,0.0003855652,0.0001221782,0.0001714208,0.00003262237,0.0004529391,0.0001400793,0.00004321794],"category_scores_gemma":[0.00009756636,0.0002350229,0.0001113132,0.0001668908,0.00008992301,0.0003204405,0.0001631347,0.0001584345,0.000005530072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009679881,"about_ca_system_score_gemma":0.00008311378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002552421,"about_ca_topic_score_gemma":0.000003852914,"domain_scores_codex":[0.9984245,0.0001448875,0.0003351475,0.0005305211,0.000199414,0.000365553],"domain_scores_gemma":[0.9984796,0.0005643817,0.0002335182,0.0003835358,0.0002644097,0.00007456923],"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":[0.00117905,0.0005661294,0.0001404124,0.0001270425,0.001673209,0.0000928588,0.001052932,0.510193,0.3938826,0.05246698,0.002802965,0.03582288],"study_design_scores_gemma":[0.0008812402,0.00004976712,0.0007154895,0.00007198635,0.00003207043,0.000002323738,0.00001471671,0.6087074,0.3799834,0.009328371,0.00008479835,0.0001284494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002384217,0.00002210417,0.9443898,0.0001997416,0.00008410722,0.0002246,0.0001105385,0.0002755951,0.05230929],"genre_scores_gemma":[0.9892344,0.000009034626,0.008873695,0.0001585932,0.0000372151,0.00009500464,0.0000308426,0.000004711081,0.001556473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9868502,"threshold_uncertainty_score":0.9583958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004873574246316249,"score_gpt":0.1898313536653862,"score_spread":0.1849577794190699,"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."}}