{"id":"W2033453524","doi":"10.1109/tcst.2014.2334472","title":"Model Predictive Quality Control of Polymethyl Methacrylate","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Model predictive control; Control theory (sociology); Trajectory; Process (computing); Controller (irrigation); Polymethyl methacrylate; Computer science; Quality (philosophy); Process control; Control (management); Artificial intelligence; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007756354,0.0003785771,0.001071225,0.0007426984,0.0001242483,0.00002441146,0.0003447664,0.0006421562,0.00001089113],"category_scores_gemma":[0.00003811917,0.0003673569,0.0002742187,0.0004138809,0.0001578085,0.0001213503,8.933051e-7,0.0005731932,0.00005028555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001447095,"about_ca_system_score_gemma":0.00003230951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001318601,"about_ca_topic_score_gemma":0.00008365657,"domain_scores_codex":[0.9974644,0.0002876586,0.001019391,0.000402275,0.0003430009,0.0004832519],"domain_scores_gemma":[0.9983501,0.0003861804,0.0002168941,0.0007489839,0.0001734856,0.0001243468],"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":[0.0001950911,0.00006871804,0.00001964996,0.0001094759,0.0005097013,9.575458e-7,0.00005388431,0.8753184,0.113198,0.001612688,0.00002712475,0.008886329],"study_design_scores_gemma":[0.004573986,0.0003220783,0.00001467777,0.00006733687,0.0001366022,0.00001992798,0.0001506796,0.9780562,0.01555328,0.000241473,0.0005550705,0.0003086728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02209524,0.0005512412,0.97105,0.0001817327,0.001978377,0.0009464359,0.0002291594,0.001776288,0.001191587],"genre_scores_gemma":[0.9988198,0.00001920191,0.00009272274,0.00005064561,0.00006998101,0.0006437963,6.214974e-7,0.0000696109,0.0002336275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9767246,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01023124826878393,"score_gpt":0.233893347251629,"score_spread":0.2236620989828451,"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."}}