{"id":"W2008597101","doi":"10.1016/j.tust.2005.12.086","title":"Numerical approach for a rock mechanics descriptive model","year":2006,"lang":"en","type":"article","venue":"Tunnelling and Underground Space Technology","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Rock mass classification; Constitutive equation; Geotechnical engineering; Brittleness; Rock mechanics; Discrete element method; Engineering; Structural engineering; Geology; Scale (ratio); Finite element method; Mathematics; Mechanics; Materials science; Physics; Composite material","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":[0.0003792947,0.0003758361,0.0004878473,0.0006217589,0.0005828011,0.0009274933,0.001522238,0.0009135542,0.004905369],"category_scores_gemma":[0.001517949,0.0003320061,0.0005777621,0.0004280479,0.0007054124,0.0007589824,0.001081963,0.0008565423,0.0008222653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006833145,"about_ca_system_score_gemma":0.001199736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004879579,"about_ca_topic_score_gemma":0.004281822,"domain_scores_codex":[0.9998036,0.00003714098,0.00001242828,0.00002875872,0.0001060766,0.00001199276],"domain_scores_gemma":[0.9997322,0.00008257671,0.00002584771,0.00004753532,0.00009646142,0.00001536704],"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":[0.00001620099,0.00006107621,0.0002970892,0.00006945915,0.00001083906,0.0001067696,0.0001267266,0.6918203,0.006484992,0.2881238,0.0009370996,0.01194565],"study_design_scores_gemma":[0.000005514201,0.000006839783,0.00003544265,0.000003312377,0.000003255709,0.00001641785,0.00001161759,0.9858842,0.0003486914,0.01145163,0.002229709,0.000003214264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005597461,0.00003123198,0.9854709,0.0001849245,0.00002708264,0.00005935946,0.00009852677,0.0001368899,0.008393589],"genre_scores_gemma":[0.3716072,0.0003705862,0.5914866,0.000230338,0.0001045193,0.0006192589,0.0005338702,0.0003133515,0.03473435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004905369,"threshold_uncertainty_score":0.01641011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009911744245488189,"score_gpt":0.1880936478013511,"score_spread":0.1781819035558629,"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."}}