{"id":"W2026516402","doi":"10.1115/gt2009-59419","title":"Verification of a Neural Network Based Predictive Emission Monitoring Module for an RB211-24C Gas Turbine","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Sensor Technologies Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada); Nova Chemicals (Canada)","funders":"","keywords":"Compressor station; Gas compressor; Natural gas; Turbine; Artificial neural network; Range (aeronautics); Condition monitoring; NOx; Engineering; Environmental science; Automotive engineering; Stack (abstract data type); Computer science; Mechanical engineering; Aerospace engineering; Electrical engineering; Combustion","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007687243,0.0007734527,0.0004717694,0.0002580438,0.0004567119,0.0004788355,0.001212507,0.0006084458,0.00132072],"category_scores_gemma":[0.001583009,0.0003005705,0.0003443238,0.0001410835,0.0003726347,0.0004400446,0.0003202616,0.0005977742,0.000290131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330781,"about_ca_system_score_gemma":0.001457287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.056137,"about_ca_topic_score_gemma":0.03620043,"domain_scores_codex":[0.9997053,0.00004917434,0.00001833817,0.0000805786,0.0001154191,0.0000312682],"domain_scores_gemma":[0.9995046,0.0002121742,0.00004296966,0.00004912669,0.000171303,0.00001980077],"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":[0.0005032331,0.0003652168,0.01406226,0.0001247708,0.00007650864,0.0002019686,0.00008935131,0.916947,0.03521129,0.0004330555,0.0005332193,0.03145208],"study_design_scores_gemma":[0.00002575771,0.0001304786,0.00248357,0.00000337246,0.00001249898,0.00001450352,0.00001242721,0.9806318,0.01643637,0.00005146874,0.0001883349,0.00000945625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.943406,0.00005967739,0.05142666,0.0001635052,0.0000426841,0.0001535896,0.0003718224,0.001583341,0.002792675],"genre_scores_gemma":[0.9928724,0.00001645574,0.00616419,0.00001342981,0.00000157991,0.00003806081,0.0001256941,0.00001643783,0.0007517872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.056137,"threshold_uncertainty_score":0.1116205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988719399504258,"score_gpt":0.2978117758284651,"score_spread":0.2679245818334225,"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."}}