{"id":"W1974969228","doi":"10.1007/s00603-014-0567-z","title":"Reliable Support Design for Excavations in Brittle Rock Using a Global Response Surface Method","year":2014,"lang":"en","type":"article","venue":"Rock Mechanics and Rock Engineering","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Hatch (Canada)","funders":"","keywords":"Spall; Brittleness; Structural engineering; Finite element method; Rock mass classification; Reliability (semiconductor); Excavation; Geotechnical engineering; Engineering; Computer science; Materials science","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":[0.0007726674,0.0008192581,0.001199548,0.0006104332,0.0003833205,0.0007111134,0.001216563,0.001431287,0.002984643],"category_scores_gemma":[0.00236761,0.0006155859,0.0006514808,0.0003284518,0.0007463202,0.0006833676,0.001202107,0.0007261522,0.0005390893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002428197,"about_ca_system_score_gemma":0.0007302514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001616768,"about_ca_topic_score_gemma":0.001536616,"domain_scores_codex":[0.9995511,0.0001188607,0.00002006065,0.00005747475,0.0002113262,0.00004111964],"domain_scores_gemma":[0.9992923,0.0003236916,0.00006890352,0.00009531584,0.0001880027,0.00003191557],"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":[0.00006867291,0.00002365711,0.0002442555,0.00005526771,0.00001484354,0.00006485045,0.00005736398,0.967061,0.007208272,0.002716778,0.0003163512,0.02216872],"study_design_scores_gemma":[0.00000616772,0.00002534973,0.0000320682,0.000001838399,0.000002502312,0.000005751716,0.000006785981,0.9987974,0.0005022136,0.0004477752,0.0001698984,0.000002155802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02332022,0.0000645301,0.9749715,0.0000621636,0.00001584032,0.00003165027,0.00002470988,0.0002607375,0.00124862],"genre_scores_gemma":[0.8263928,0.0001069756,0.1703099,0.00003782455,0.00002242199,0.0001886483,0.00009529344,0.0001874085,0.002658719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002984643,"threshold_uncertainty_score":0.009984612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246940139935526,"score_gpt":0.253113133911773,"score_spread":0.2306437325124177,"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."}}