{"id":"W4285038138","doi":"10.1016/j.ijrmms.2022.105145","title":"Numerical modelling of rock mass bulking and geometric dilation using a bonded block modelling approach to assist in support design for deep mining pillars","year":2022,"lang":"en","type":"article","venue":"International Journal of Rock Mechanics and Mining Sciences","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Spall; Rock mass classification; Brittleness; Geotechnical engineering; Structural engineering; Rockfall; Computer simulation; Engineering; Shearing (physics); Mining engineering; Geology; Landslide; Materials science; Simulation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001502464,0.0001531184,0.0002972808,0.001034208,0.0002447907,0.00009864356,0.000322275,0.00004848769,0.000002030032],"category_scores_gemma":[0.00007583857,0.0001591789,0.00006696069,0.0005191437,0.000003200065,0.0002512409,0.0001049371,0.0001592491,3.154625e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264064,"about_ca_system_score_gemma":0.00008748595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009619583,"about_ca_topic_score_gemma":4.648564e-7,"domain_scores_codex":[0.9981616,0.00003253495,0.0006517961,0.0002438366,0.0006521523,0.0002581127],"domain_scores_gemma":[0.9991632,0.0001954865,0.0002970893,0.00005426459,0.0002051349,0.00008489259],"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":[0.00004154992,0.00002479676,0.00003195893,0.00001932174,0.00003675231,0.000003621982,0.00113698,0.9958532,0.001553226,0.0006685948,0.000004976088,0.0006249471],"study_design_scores_gemma":[0.0003622289,0.0002378182,6.841713e-7,0.00008330322,0.00002608004,0.0001318563,0.001581253,0.9949743,0.0005703638,0.001829405,0.00003487425,0.0001678921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2687719,0.0003299501,0.7303967,0.00002176093,0.000345922,0.0001058428,0.000004921698,0.000007443086,0.00001554997],"genre_scores_gemma":[0.7682373,0.00006478039,0.231595,0.00002422944,0.00004962421,0.000007774052,0.000001236588,0.00001710375,0.00000294359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4994654,"threshold_uncertainty_score":0.6491129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07171133848907368,"score_gpt":0.2667801375084274,"score_spread":0.1950687990193537,"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."}}