{"id":"W4403676711","doi":"10.1109/case59546.2024.10711335","title":"Automated Drill and Blast Design using Data from Autonomous Drills*","year":2024,"lang":"en","type":"article","venue":"","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rio Tinto","keywords":"Drill; Computer science; Engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001224138,0.0008007632,0.0006175999,0.001237506,0.0003703986,0.0007498797,0.0008107233,0.0006024403,0.00132637],"category_scores_gemma":[0.004550378,0.0008090945,0.0005366031,0.0008536446,0.0005029152,0.0007256683,0.000454256,0.0003927883,0.000234097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009721438,"about_ca_system_score_gemma":0.001068752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009691551,"about_ca_topic_score_gemma":0.02166553,"domain_scores_codex":[0.9990579,0.0002924617,0.00005514685,0.000136304,0.0003868547,0.00007127439],"domain_scores_gemma":[0.9963864,0.001877716,0.0004449157,0.000390407,0.0008185274,0.00008204042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002528891,0.0002044491,0.01187,0.0001292892,0.0000314462,0.0001375729,0.0001125064,0.9248267,0.005811606,0.000337927,0.0004681836,0.0558175],"study_design_scores_gemma":[0.00004915409,0.0002195622,0.006342077,0.000009468345,0.00001892473,0.00004047078,0.00008091104,0.9860308,0.00555812,0.0006153935,0.001015633,0.00001939503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8765922,0.0001220545,0.1177265,0.00009355233,0.00001942757,0.0002654235,0.000947822,0.0008714138,0.003361625],"genre_scores_gemma":[0.9322802,0.00003830809,0.06593307,0.000008371473,0.000002265355,0.0001305146,0.00103244,0.00004265799,0.0005322613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009691551,"threshold_uncertainty_score":0.01927024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05549854640194285,"score_gpt":0.2624200294838213,"score_spread":0.2069214830818785,"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."}}