{"id":"W2788055376","doi":"10.1016/j.ijrmms.2018.01.021","title":"Use of an integrated finite/discrete element method-discrete fracture network approach to characterize surface subsidence associated with sub-level caving","year":2018,"lang":"en","type":"article","venue":"International Journal of Rock Mechanics and Mining Sciences","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of British Columbia; Golder Associates (Canada)","funders":"","keywords":"Inclinometer; Discontinuity (linguistics); Geology; Groundwater-related subsidence; Fracture (geology); Deformation (meteorology); Subsidence; Displacement (psychology); Discrete element method; Underground mining (soft rock); Finite element method; Surface (topology); Geotechnical engineering; Mining engineering; Coal mining; Engineering; Structural engineering; Geodesy; Mechanics; Geometry; Coal","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":[0.0002122086,0.0003409448,0.0003839896,0.0008960903,0.0003112802,0.000391727,0.0005435565,0.0005826082,0.0006704706],"category_scores_gemma":[0.0007207556,0.0002430143,0.0003210234,0.000448648,0.0003256574,0.00040936,0.0003887363,0.0003279734,0.0001014807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003458958,"about_ca_system_score_gemma":0.0005179558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006048843,"about_ca_topic_score_gemma":0.01103455,"domain_scores_codex":[0.9999254,0.0000110781,0.000004751683,0.00001723679,0.00003226701,0.000009235435],"domain_scores_gemma":[0.9996724,0.0001566692,0.00004448223,0.00002738169,0.00007464598,0.00002451943],"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":[0.0001152044,0.0002680528,0.01996578,0.00005641193,0.00004788925,0.0001447017,0.00009293574,0.9008777,0.03059024,0.00247568,0.0001579099,0.04520752],"study_design_scores_gemma":[0.000001583212,0.00001122796,0.0010726,9.84626e-7,0.00000307314,0.00001013772,0.000006947879,0.9982213,0.0005187234,0.0001164675,0.0000344497,0.000002421181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5359669,0.00009764213,0.4604268,0.00006228944,0.00002448748,0.00008206179,0.0001834763,0.000338314,0.002818016],"genre_scores_gemma":[0.9521105,0.00003751015,0.04716411,0.000009086049,0.000004395193,0.00003446898,0.00009443406,0.00002258492,0.0005229146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006048843,"threshold_uncertainty_score":0.01202732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05289385434053408,"score_gpt":0.2824936948525358,"score_spread":0.2295998405120017,"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."}}