{"id":"W2744773669","doi":"10.1007/s00603-017-1293-0","title":"Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods","year":2017,"lang":"en","type":"article","venue":"Rock Mechanics and Rock Engineering","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"ArcelorMittal (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; ArcelorMittal","keywords":"Rock mass classification; Kriging; Geology; Geostatistics; Spatial variability; Rock mass rating; Field (mathematics); Geotechnical engineering; Soil science; Statistics; Mathematics","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":[0.001849967,0.0006644628,0.0008092996,0.001016299,0.0005793982,0.001450772,0.002128404,0.001717816,0.002299813],"category_scores_gemma":[0.00868659,0.001032754,0.001366528,0.0009872236,0.001494021,0.001570303,0.001999259,0.001315425,0.0002114212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330127,"about_ca_system_score_gemma":0.001814819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03357238,"about_ca_topic_score_gemma":0.02518684,"domain_scores_codex":[0.9994124,0.0002447653,0.00003102469,0.0001304255,0.00008925006,0.00009224541],"domain_scores_gemma":[0.9937364,0.004794413,0.000581063,0.0003424983,0.0003144035,0.0002311749],"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":[0.0000105671,0.00001426227,0.001189887,0.00000571691,0.00001533338,0.00001518331,0.00001465698,0.9949095,0.000107594,0.002982853,0.00003650599,0.0006979846],"study_design_scores_gemma":[0.000003369169,0.00000330556,0.0001770866,9.136466e-7,0.000002991746,0.000002889169,0.000002911241,0.9987094,0.00004506359,0.001024849,0.00002405916,0.000003109734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4379538,0.0001301372,0.5575732,0.0003515763,0.0000419631,0.0001006044,0.0004157657,0.0003890875,0.003043847],"genre_scores_gemma":[0.9737815,0.00006228053,0.02411324,0.00004029601,0.00001682355,0.00007707785,0.0002508814,0.00006878643,0.001589106],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03357238,"threshold_uncertainty_score":0.06675392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03773031069983884,"score_gpt":0.3024762281214777,"score_spread":0.2647459174216388,"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."}}