{"id":"W2924615849","doi":"10.1139/tcsme-2017-0135","title":"Structure analysis of a dragline tooth and its wear prediction","year":2019,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"von Mises yield criterion; Materials science; Finite element method; Deformation (meteorology); Structural engineering; Safety factor; Overburden; Workbench; Enhanced Data Rates for GSM Evolution; Fracture (geology); Cracking; Stress (linguistics); Metallurgy; Composite material; Engineering; Geotechnical engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000091009,0.0001057322,0.0002260494,0.0000999606,0.00006483131,0.000006039121,0.0001167839,0.0001557839,0.00003464354],"category_scores_gemma":[0.00001087863,0.0000947735,0.0003905194,0.0004879018,0.000005466367,0.00004898443,0.000003490862,0.0001721325,1.786699e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009625294,"about_ca_system_score_gemma":0.00003985771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005242245,"about_ca_topic_score_gemma":0.004409222,"domain_scores_codex":[0.9994108,0.000003417211,0.0001977098,0.0001100477,0.0001010338,0.0001770122],"domain_scores_gemma":[0.9996105,0.00004228078,0.00002438558,0.0001720607,0.00004403141,0.0001067009],"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":[0.000001945641,0.000003126919,0.00000400079,0.0001797596,0.0007753877,2.431702e-8,0.0002369961,0.9274352,0.06992854,0.001216924,0.00001133218,0.0002067957],"study_design_scores_gemma":[0.0001876485,0.00002179666,0.00006057772,0.00003218586,0.0005785878,0.0000011953,0.0000616441,0.9580166,0.04062066,0.00004451595,0.0002896709,0.00008488588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6987439,0.0003690569,0.2978677,0.0000989567,0.0008696963,0.000440347,0.001476698,0.0001210354,0.00001255942],"genre_scores_gemma":[0.9976015,0.00003488762,0.00224689,0.00001169976,0.00001809174,0.000006520003,0.000009527894,0.00002390264,0.00004696042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2988576,"threshold_uncertainty_score":0.3864751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004597616896573005,"score_gpt":0.171160050762125,"score_spread":0.166562433865552,"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."}}