{"id":"W2463694888","doi":"10.1080/14749009.2016.1199296","title":"Discrete fracture network based drift stability at the Éléonore mine","year":2016,"lang":"en","type":"article","venue":"Mining Technology Transactions of the Institutions of Mining and Metallurgy Section A","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Université Laval","funders":"","keywords":"Stability (learning theory); Parametric statistics; Fracture (geology); Sensitivity (control systems); Geology; Rock mass classification; Excavation; Series (stratigraphy); Photogrammetry; Parametric model; Geotechnical engineering; Mining engineering; Computer science; Engineering; Statistics; Mathematics; Remote sensing; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004132964,0.0001920959,0.000248343,0.001115192,0.0005569702,0.0006609975,0.0007135951,0.0007213207,0.000547467],"category_scores_gemma":[0.001105439,0.000240829,0.0002322812,0.0005934346,0.0005887813,0.0004498576,0.0003922064,0.0003793786,0.0000906223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003019436,"about_ca_system_score_gemma":0.001067883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1622796,"about_ca_topic_score_gemma":0.2419747,"domain_scores_codex":[0.9998435,0.00002324252,0.000008981991,0.00005113508,0.00005184725,0.00002131684],"domain_scores_gemma":[0.9996746,0.0001356039,0.0000663018,0.00002027966,0.00007635747,0.00002696423],"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":[0.0001088309,0.00003315681,0.07580286,0.00004532833,0.00002811085,0.000311624,0.0002086549,0.9084427,0.00466811,0.001946195,0.0001469031,0.008257544],"study_design_scores_gemma":[0.000005930293,0.00002698015,0.03563155,0.000009921101,0.000006184916,0.0000740149,0.0001663723,0.9616371,0.001226837,0.0009997492,0.0001968187,0.0000184681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955323,0.00004224435,0.003347708,0.00003104156,0.000001231692,0.000008622298,0.0002587953,0.00001924788,0.000758978],"genre_scores_gemma":[0.99823,0.00002830938,0.001361596,0.000001776422,3.232058e-7,0.000003528736,0.00009655781,0.000002337897,0.0002755381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1622796,"threshold_uncertainty_score":0.32267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589023920581211,"score_gpt":0.2158359441428502,"score_spread":0.1999457049370381,"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."}}