{"id":"W4322729438","doi":"10.1016/j.compgeo.2023.105348","title":"Numerical simulation of long-term performance of deep geological repository placement rooms in crystalline and sedimentary rocks","year":2023,"lang":"en","type":"article","venue":"Computers and Geotechnics","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nuclear Waste Management Organization","funders":"Nuclear Waste Management Organization","keywords":"Rock mass classification; Geotechnical engineering; Computer simulation; Radioactive waste; Geology; Pore water pressure; Sedimentary rock; Overburden pressure; Environmental science; Petroleum engineering; Engineering; Waste management; Simulation; Geochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000609679,0.0005585859,0.0008057437,0.0008586506,0.001052816,0.001283752,0.001423009,0.002078878,0.003530238],"category_scores_gemma":[0.003309427,0.0007082141,0.000694793,0.001051343,0.001635032,0.0008312747,0.0008691628,0.001062018,0.0002626164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002287524,"about_ca_system_score_gemma":0.001507324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04611629,"about_ca_topic_score_gemma":0.02700089,"domain_scores_codex":[0.9996496,0.00005990474,0.00002067814,0.00006411585,0.00005769851,0.0001478937],"domain_scores_gemma":[0.99677,0.001933213,0.0002880033,0.0001458347,0.0003399456,0.0005230012],"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":[0.00009033013,0.0001152846,0.003704222,0.00001545375,0.00001368905,0.00007622565,0.00003681752,0.9934137,0.000957526,0.0003816338,0.0001847084,0.001010393],"study_design_scores_gemma":[0.00001188352,0.0000499151,0.001247804,0.000002997223,0.000005084833,0.000009834397,0.00006448107,0.9980761,0.000362303,0.0001019751,0.00006060291,0.000007023683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935695,0.00008531987,0.002797433,0.0001748961,0.00002818105,0.00001818482,0.000290021,0.00009718982,0.002939268],"genre_scores_gemma":[0.9980022,0.00002808666,0.0009320651,0.00001615923,0.000003563775,0.00001005858,0.0001603745,0.00001411371,0.0008334063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04611629,"threshold_uncertainty_score":0.09169573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009352132325334392,"score_gpt":0.2132592632007473,"score_spread":0.2039071308754129,"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."}}