{"id":"W2769200991","doi":"10.36487/acg_rep/1710_44_hauta","title":"Application of the GeoSequencing Module to ensure optimised underground mine schedules with reduced geotechnical risk","year":2017,"lang":"en","type":"article","venue":"","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Excellence in Mining Innovation","funders":"Vale Canada Limited","keywords":"Geotechnical engineering; Mining engineering; Geology; Civil engineering; Engineering","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":[0.000788952,0.000695531,0.000389485,0.0005128434,0.0003027184,0.0005748497,0.000787863,0.0005458989,0.006635227],"category_scores_gemma":[0.002227977,0.0004560835,0.0004486773,0.0002992381,0.0002803622,0.0004924719,0.0006619869,0.0004645773,0.0007058235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006973344,"about_ca_system_score_gemma":0.001831821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695394,"about_ca_topic_score_gemma":0.003701818,"domain_scores_codex":[0.9995974,0.00005572677,0.00001893844,0.00007579078,0.000206665,0.00004557039],"domain_scores_gemma":[0.999494,0.0001665477,0.00008014065,0.00005901672,0.0001681002,0.00003218816],"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":[0.0001227304,0.0000799388,0.0008990415,0.0001333004,0.00001850362,0.0001551356,0.0001007765,0.9030869,0.03761823,0.004912953,0.001888846,0.05098369],"study_design_scores_gemma":[0.00003703691,0.0001340696,0.0005487628,0.00001779153,0.00001307309,0.00006049585,0.00003183466,0.9638214,0.02736964,0.00168875,0.006257724,0.00001939954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1211288,0.00009184096,0.8560896,0.0001390659,0.00005960836,0.0003714369,0.0004526405,0.006680756,0.01498636],"genre_scores_gemma":[0.4888766,0.00007810444,0.5042226,0.00005589565,0.0000109986,0.0003946438,0.0006389045,0.0009303899,0.004791809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006635227,"threshold_uncertainty_score":0.02219701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01301281830308565,"score_gpt":0.2213916464417406,"score_spread":0.208378828138655,"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."}}