{"id":"W4393859978","doi":"10.1002/cjce.25258","title":"Explosion pressure and duration prediction using machine learning: A comparative study using classical models with <scp>Adam‐</scp> optimized neural network","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Combustion and Detonation Processes","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Yayasan UTP; Majlis Amanah Rakyat; Universiti Teknologi Petronas","keywords":"Artificial neural network; Duration (music); Artificial intelligence; Machine learning; Computer science; Physics","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":[0.001724683,0.001036235,0.0008314113,0.0007140835,0.0002626312,0.0009910956,0.001001329,0.00119411,0.0007717354],"category_scores_gemma":[0.003137456,0.0003152436,0.0006629656,0.0005483028,0.0003614234,0.000863574,0.0004209789,0.0008964554,0.00018558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007707955,"about_ca_system_score_gemma":0.0007515742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01232432,"about_ca_topic_score_gemma":0.004858312,"domain_scores_codex":[0.9996188,0.000130491,0.00003229103,0.00008880131,0.00008899979,0.00004056473],"domain_scores_gemma":[0.9977326,0.001591489,0.0001568208,0.00008484475,0.0003803309,0.00005391841],"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":[0.0001278806,0.0001017437,0.003468649,0.00007207614,0.00005139161,0.00004883334,0.00002317868,0.9778948,0.00051111,0.0004109167,0.000252438,0.01703692],"study_design_scores_gemma":[0.00000122106,0.00001939216,0.0002144265,0.000002718308,0.000002940008,0.000002184622,0.000002581575,0.9994981,0.0001841137,0.00004372204,0.00002686795,0.000001747031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8419469,0.002652123,0.1473339,0.0006136791,0.000166974,0.00007615725,0.0002902157,0.000826777,0.006093258],"genre_scores_gemma":[0.9916367,0.0002543744,0.007308593,0.00002680089,0.00001536438,0.00003125356,0.0001213532,0.00001504498,0.0005905158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01232432,"threshold_uncertainty_score":0.0245052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767833604591765,"score_gpt":0.2229999376391389,"score_spread":0.1953216015932212,"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."}}