{"id":"W4413240215","doi":"10.1002/adc2.70026","title":"Artificial Neural Networks and Experimental Data Analysis‐Based Biomass Combustion Machine's Dynamical Model Identification","year":2025,"lang":"en","type":"article","venue":"Advanced Control for Applications","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Multilayer perceptron; Artificial neural network; Inverse; Combustion; Dimension (graph theory); Machine learning; Test data; Artificial intelligence; Perceptron; Mean squared error; Recurrent neural network; Experimental data; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001220944,0.0007316498,0.0004394907,0.000596214,0.0002014894,0.0005449391,0.0004685753,0.0006488409,0.0008312481],"category_scores_gemma":[0.003831979,0.0002615726,0.0005042583,0.0005035686,0.0002835812,0.0006515973,0.0002863838,0.0006759852,0.0001871744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006673666,"about_ca_system_score_gemma":0.0005044434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00956443,"about_ca_topic_score_gemma":0.005465261,"domain_scores_codex":[0.9996153,0.0001417449,0.00003527715,0.00007697057,0.0001064032,0.00002431809],"domain_scores_gemma":[0.9986194,0.0008367088,0.0001484953,0.00008762801,0.0002914712,0.00001629882],"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":[0.00008104829,0.00007461267,0.003011768,0.00008340307,0.00004551634,0.00004947541,0.00003811652,0.962233,0.004926909,0.0005549951,0.0002245301,0.0286766],"study_design_scores_gemma":[0.000001087809,0.00000919597,0.000446489,0.000002802946,0.000002205366,0.000002607658,0.000002568226,0.9982462,0.001123987,0.0001129186,0.00004702003,0.000002884636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5531651,0.0005403362,0.439947,0.000295483,0.0001128069,0.0001039565,0.0004459733,0.001533047,0.003856124],"genre_scores_gemma":[0.9828151,0.00006652989,0.01638619,0.0000149615,0.000006346985,0.0000526229,0.0001757308,0.00001814588,0.0004642938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00956443,"threshold_uncertainty_score":0.01901752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03438501631485746,"score_gpt":0.3174673387112561,"score_spread":0.2830823223963986,"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."}}