{"id":"W2587922656","doi":"","title":"Validation of empirical rock mass classification systems for rock slopes","year":2016,"lang":"en","type":"article","venue":"3rd International Symposium on Mine Safety Science and Engineering","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Rock mass rating; Rock mass classification; Classification of discontinuities; Geological Strength Index; Geology; Stability (learning theory); Excavation; Rock mechanics; Groundwater; Geotechnical engineering; Mining engineering; Mathematics; Computer science; Machine learning","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":[0.009143061,0.0008422771,0.0004790768,0.004472514,0.0004761082,0.001354534,0.001428642,0.0008849748,0.001807583],"category_scores_gemma":[0.04166656,0.0001836732,0.0007192886,0.002491855,0.0008166622,0.00106365,0.001001814,0.0005950463,0.0007933007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068412,"about_ca_system_score_gemma":0.0006328709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004513429,"about_ca_topic_score_gemma":0.004068551,"domain_scores_codex":[0.9935184,0.002906448,0.0006085521,0.0009988736,0.00176382,0.0002038602],"domain_scores_gemma":[0.9590212,0.01974669,0.004890834,0.004160285,0.01169366,0.0004873577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001319031,0.00145874,0.6814784,0.000645656,0.0004013793,0.0003314389,0.002311262,0.08408965,0.007174914,0.002693915,0.003317004,0.2147786],"study_design_scores_gemma":[0.0001410929,0.001250102,0.4418658,0.0002559584,0.0001139969,0.0001947908,0.003211878,0.5378376,0.009553489,0.001626617,0.003874604,0.00007406474],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97004,0.0001228471,0.02486192,0.0000354605,0.00003804498,0.0003558543,0.000881819,0.0001981494,0.003465855],"genre_scores_gemma":[0.9810238,0.00004579576,0.01693694,0.000009766152,0.000008595189,0.0001944291,0.001339256,0.00001738713,0.000424159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009143061,"threshold_uncertainty_score":0.04835367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01237752418817095,"score_gpt":0.244317540673994,"score_spread":0.231940016485823,"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."}}