{"id":"W4237106617","doi":"10.1504/ijhm.2020.105499","title":"Machine learning model for dynamical response of nano-composite pipe conveying fluid under seismic loading","year":2020,"lang":"en","type":"article","venue":"International Journal of Hydromechatronics","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Backpropagation; Mean squared error; Displacement (psychology); Estimator; Support vector machine; Artificial neural network; RADIUS; Correlation coefficient; Coefficient of determination; Mathematics; Computer science; Structural engineering; Engineering; Statistics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004173744,0.0006028035,0.0004784651,0.0003560435,0.0002459515,0.0003921145,0.0005483862,0.0008621694,0.001175821],"category_scores_gemma":[0.0007768814,0.0002487511,0.0004774714,0.0002624467,0.0003065431,0.0004799524,0.0002588473,0.0006094879,0.0001888043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004878613,"about_ca_system_score_gemma":0.0006567189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008585916,"about_ca_topic_score_gemma":0.005943742,"domain_scores_codex":[0.999864,0.00002639268,0.000009674828,0.00004716752,0.00003370573,0.00001902462],"domain_scores_gemma":[0.9997144,0.0001464369,0.00004422645,0.000011194,0.0000770183,0.000006747367],"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":[0.00002401975,0.00002218548,0.0009096955,0.00003789632,0.00001236191,0.00004105948,0.00002518999,0.9889812,0.002246289,0.0004555682,0.0001175969,0.007126884],"study_design_scores_gemma":[5.917024e-7,0.000006371619,0.0001279784,0.000001030265,9.676171e-7,0.00000260145,0.000001501582,0.9995781,0.0001793075,0.0000737771,0.00002675276,0.000001129758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2855152,0.0005731419,0.7064085,0.0003926565,0.00007171454,0.00009212959,0.000317718,0.00085593,0.005772962],"genre_scores_gemma":[0.9848526,0.0001528351,0.01174704,0.00002871342,0.00001020769,0.0001399242,0.0001509984,0.00001407019,0.002903657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008585916,"threshold_uncertainty_score":0.0170719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009923386343839043,"score_gpt":0.2264481453651613,"score_spread":0.2165247590213223,"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."}}