{"id":"W3210242289","doi":"10.3390/en14216928","title":"An Attempt to Use Machine Learning Algorithms to Estimate the Rockburst Hazard in Underground Excavations of Hard Coal Mine","year":2021,"lang":"en","type":"article","venue":"Energies","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Ministerstwo Edukacji i Nauki","keywords":"Rock mass classification; Excavation; Artificial neural network; Coal mining; Mining engineering; Underground mining (soft rock); Rock burst; Decision tree; Engineering; Hazard; Random forest; Gradient boosting; Geotechnical engineering; Machine learning; Coal; Computer 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":[0.00119152,0.0007618872,0.0007941346,0.001879651,0.0003043546,0.0007071862,0.0006607317,0.0009259763,0.0004097537],"category_scores_gemma":[0.003168059,0.0002460277,0.0006137702,0.0008718303,0.0001887688,0.0008804514,0.0004186029,0.0005631096,0.0001599449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003491371,"about_ca_system_score_gemma":0.0007062158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005259455,"about_ca_topic_score_gemma":0.003238676,"domain_scores_codex":[0.9995951,0.00009103968,0.00005003571,0.000122987,0.00008867245,0.00005217051],"domain_scores_gemma":[0.9988859,0.000559672,0.0001770286,0.00006015993,0.0002804262,0.00003674145],"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":[0.0001645808,0.0003493807,0.07137667,0.0001441874,0.0001489408,0.0001749835,0.0001098833,0.6448368,0.004784463,0.001258455,0.000984885,0.2756667],"study_design_scores_gemma":[0.000004863848,0.00004355962,0.006310919,0.00001073894,0.00001626731,0.00003714708,0.00003050645,0.9916779,0.001057851,0.0006485529,0.0001530815,0.000008702731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4226316,0.0007799281,0.5736736,0.000256415,0.00006100052,0.0001064398,0.000268193,0.0007908781,0.001431934],"genre_scores_gemma":[0.8911561,0.0002582415,0.1074523,0.00004898029,0.0000267997,0.00008250464,0.0003286545,0.00001645504,0.0006299753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005259455,"threshold_uncertainty_score":0.01045769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586394250970844,"score_gpt":0.2761590734549907,"score_spread":0.2502951309452823,"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."}}