{"id":"W4392103847","doi":"10.1007/978-3-031-48821-4_20","title":"Class-C Simulations of LEAP-ASIA-2019 via OpenSees Platform by Using a Pressure Dependent Multi-yield Surface Model","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Geotechnical Engineering and Soil Mechanics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Higher Education Discipline Innovation Project; Zhejiang University; Tsinghua University; National Natural Science Foundation of China","keywords":"OpenSees; Yield (engineering); Class (philosophy); Computer science; Environmental science; Materials science; Composite material; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003151165,0.0005531178,0.0004771529,0.0003853067,0.0004461239,0.0007776135,0.001153241,0.0009567856,0.005790436],"category_scores_gemma":[0.0008071858,0.0002259341,0.0004888577,0.0004690534,0.0004020575,0.0004241253,0.0005365213,0.0007177007,0.0005514604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007652978,"about_ca_system_score_gemma":0.000690324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01746137,"about_ca_topic_score_gemma":0.0138654,"domain_scores_codex":[0.9998626,0.00002729955,0.000006031684,0.00001854459,0.00005337458,0.00003209716],"domain_scores_gemma":[0.9995791,0.0002128162,0.0000266353,0.00003914101,0.0001137807,0.00002838522],"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":[0.000040928,0.00005363737,0.001394311,0.00004295972,0.00001163499,0.00008873136,0.00004543167,0.9893613,0.001863651,0.001949881,0.001178942,0.003968463],"study_design_scores_gemma":[0.000007816401,0.00001718203,0.0003582296,0.000004206675,0.000002690919,0.000009385363,0.00002418419,0.9977259,0.0007385963,0.0002474038,0.0008602541,0.00000427723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8645821,0.0001709684,0.04973287,0.0004235018,0.0001710007,0.0001503689,0.003293572,0.002121629,0.07935394],"genre_scores_gemma":[0.9642474,0.0001333654,0.02396507,0.00008712643,0.00001828169,0.0002003139,0.002244089,0.0003345929,0.008769755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01746137,"threshold_uncertainty_score":0.03471947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03286001612128108,"score_gpt":0.2325823808087113,"score_spread":0.1997223646874302,"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."}}