{"id":"W4386289799","doi":"10.1002/cjce.25080","title":"A deep graph convolutional network model of <scp>NOx</scp> emission prediction for coal‐fired boiler","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"NOx; Boiler (water heating); Computer science; Graph; Process engineering; Combustion; Engineering; Theoretical computer science; Chemistry; Waste management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002410746,0.0006545151,0.0003924546,0.0004375275,0.0003285298,0.0004582327,0.0008545471,0.0007020269,0.001466816],"category_scores_gemma":[0.0004846996,0.0003450119,0.0006609213,0.0004072945,0.0002905387,0.0004995476,0.0003593615,0.0006918338,0.0001996809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108154,"about_ca_system_score_gemma":0.001004693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07140519,"about_ca_topic_score_gemma":0.04839815,"domain_scores_codex":[0.9999064,0.00001133154,0.000003902583,0.00003333169,0.00001981111,0.00002523183],"domain_scores_gemma":[0.9998709,0.00004102819,0.00001488865,0.000008191596,0.00005476326,0.00001024433],"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":[0.0000444446,0.00003665926,0.001506347,0.0000185598,0.00002932525,0.00005295527,0.00001106488,0.9818971,0.001647246,0.0009332722,0.0004883396,0.01333469],"study_design_scores_gemma":[6.074368e-7,0.000002461232,0.0001351779,5.95797e-7,0.00000223336,0.000001288822,5.674627e-7,0.9996192,0.0001102486,0.00009929842,0.0000272444,9.024597e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5297461,0.001231561,0.4556691,0.0008862054,0.0002086309,0.00005186968,0.00076607,0.001718525,0.009721846],"genre_scores_gemma":[0.9865366,0.0001704428,0.009588393,0.00005045178,0.00001317854,0.00002677624,0.0003776328,0.0000201838,0.003216346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07140519,"threshold_uncertainty_score":0.1419792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074052301175132,"score_gpt":0.2040674983586817,"score_spread":0.1833269753469303,"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."}}