{"id":"W4412461761","doi":"10.1016/j.tust.2025.106901","title":"Data-based assessment of rock strengths and cuttability using the monitored parameters while drilling, tunneling, and mining","year":2025,"lang":"en","type":"article","venue":"Tunnelling and Underground Space Technology","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Science and Technology Program of Hunan Province; Fundamental Research Funds for Central Universities of the Central South University; China Scholarship Council; National Natural Science Foundation of China; McGill University","keywords":"Drilling; Mining engineering; Quantum tunnelling; Geology; Geotechnical engineering; Rock mechanics; Engineering; Data mining; Petroleum engineering; Computer science; Mechanical engineering; Physics; Condensed matter physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004653687,0.0002797303,0.000416102,0.0002909211,0.0003507809,0.00007129135,0.0002806619,0.0003037584,0.000001306637],"category_scores_gemma":[0.0001357389,0.0002368943,0.00003095875,0.0004000526,0.0001666491,0.00009514287,0.0002288793,0.0004270329,1.217104e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005155651,"about_ca_system_score_gemma":0.00006443007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009127672,"about_ca_topic_score_gemma":0.000068753,"domain_scores_codex":[0.9985898,0.00005165023,0.0003831753,0.0004932221,0.000127336,0.0003548557],"domain_scores_gemma":[0.9984815,0.0006027361,0.0001032353,0.0006892785,0.00006184083,0.00006142983],"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":[0.00004217628,0.0001448021,0.03073054,0.001200941,0.0005479175,0.00001091436,0.0007717783,0.9271971,0.0122509,0.01156459,0.0001809051,0.01535743],"study_design_scores_gemma":[0.0004698051,0.00005553223,0.0001580505,0.0002321791,0.0001472283,0.00001192836,0.003290264,0.9896848,0.001750998,0.003527696,0.0004416055,0.0002299299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7332938,0.003612414,0.2619328,0.0004208826,0.0002414252,0.0001566352,0.00001953067,0.0002807032,0.00004176753],"genre_scores_gemma":[0.9716858,0.001165832,0.02702965,0.00002218907,0.00002302705,0.000007609757,0.00001100944,0.00002992827,0.00002495808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.238392,"threshold_uncertainty_score":0.9660269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02300882277672995,"score_gpt":0.2907111514356265,"score_spread":0.2677023286588966,"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."}}