{"id":"W54452884","doi":"","title":"Three Dimensional Finite Element Optimization Using the Partial p-Adaptive Method for Stress Analysis of Underground Excavations with Prismatic Cross-sections","year":2014,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Soil, Finite Element Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Concordia University","keywords":"Finite element method; Hexahedron; Geomechanics; Structural engineering; Engineering; Plane stress; Excavation; Stress field; Software; Quadratic equation; Stress (linguistics); Discrete element method; Computer science; Geotechnical engineering; Geometry; Mathematics; Mechanics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001153745,0.0003466141,0.0005898149,0.002057974,0.001000368,0.0001600109,0.00049806,0.0002655217,0.00003276285],"category_scores_gemma":[0.0001277986,0.0003226771,0.0003265936,0.003267706,0.0001937831,0.000264563,0.00007083899,0.0006672746,6.832708e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008215703,"about_ca_system_score_gemma":0.0004818974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003409103,"about_ca_topic_score_gemma":0.03694807,"domain_scores_codex":[0.9968876,0.0005932025,0.0005350278,0.0005460452,0.0008735334,0.0005645517],"domain_scores_gemma":[0.9955385,0.00253674,0.000368258,0.0006741284,0.0007510728,0.0001312513],"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":[0.0003539525,0.00006027484,0.009863631,0.0001670377,0.003306123,0.000008052287,0.0002844106,0.9834904,0.000272482,0.00208177,0.00003289109,0.0000789902],"study_design_scores_gemma":[0.0006175726,0.0002772126,0.01789107,0.0001115912,0.00212852,0.000001503475,0.001429522,0.969842,0.006917908,0.0002272931,0.0002220872,0.0003337132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2365878,0.00004293278,0.7595791,0.00001901114,0.0004045634,0.001006898,0.00009690005,0.00007957923,0.002183283],"genre_scores_gemma":[0.9181873,0.0000305809,0.07639115,0.000004466181,0.0004256027,0.0000956302,0.001472042,0.0001766492,0.003216555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6831879,"threshold_uncertainty_score":0.9999225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05110680539447867,"score_gpt":0.3371267255865735,"score_spread":0.2860199201920949,"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."}}