{"id":"W4309709481","doi":"10.1016/j.conbuildmat.2022.129703","title":"Predicting stress-strain behavior of normal weight and lightweight aggregate concrete exposed to high temperature using LSTM recurrent neural network","year":2022,"lang":"en","type":"article","venue":"Construction and Building Materials","topic":"Fire effects on concrete materials","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Materials science; Compressive strength; Composite material; Aggregate (composite); Elastic modulus; Young's modulus; Silica fume; Stress–strain curve; Modulus; Elasticity (physics); Stress (linguistics); Structural engineering; Deformation (meteorology)","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":[0.0001359648,0.0004386003,0.0003105326,0.0003040362,0.0001296826,0.0002245694,0.0003552296,0.0004759307,0.0007214806],"category_scores_gemma":[0.0003542855,0.0002102773,0.0003732384,0.0002851034,0.0001818402,0.0003253366,0.0001558191,0.0002829053,0.0001854608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004055251,"about_ca_system_score_gemma":0.0002186174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01032771,"about_ca_topic_score_gemma":0.01310319,"domain_scores_codex":[0.9999464,0.000003806969,0.000002425421,0.00001689393,0.00001560521,0.00001497105],"domain_scores_gemma":[0.9998853,0.00003336752,0.0000201224,0.00001014157,0.00003859837,0.00001239996],"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":[0.0005100739,0.000316488,0.03929256,0.00009512286,0.00008677572,0.000438803,0.0001049756,0.8187416,0.09532265,0.0003231739,0.0007526525,0.04401515],"study_design_scores_gemma":[0.000002458283,0.00003387357,0.01208591,0.000001666993,0.000007527263,0.00001250656,0.00001515726,0.9836949,0.004031316,0.00007100953,0.00003740327,0.000006325216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919876,0.00004327852,0.0072059,0.00002323593,0.00001638257,0.000004677813,0.0001395148,0.0001624663,0.0004169822],"genre_scores_gemma":[0.9989849,0.000015992,0.0006228772,0.000003276,0.00000205299,0.000002513261,0.0001138837,0.000004317847,0.0002501508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01032771,"threshold_uncertainty_score":0.02053523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007628529199980655,"score_gpt":0.2090480456551736,"score_spread":0.2014195164551929,"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."}}