{"id":"W651449872","doi":"","title":"Mechanical and Material Characterization of Mining Wheels for Enhanced Safety","year":2014,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Mechanical Failure Analysis and Simulation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Workplace Safety and Insurance Board; Government of Ontario","keywords":"Characterization (materials science); Forensic engineering; Business; Engineering; Risk analysis (engineering); Computer science; Materials science; Nanotechnology","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":[0.000394282,0.0002171093,0.0001924913,0.0008037599,0.0003238842,0.0002972432,0.0003908104,0.0003456881,0.001673131],"category_scores_gemma":[0.0006731739,0.0001901325,0.0002221101,0.0003286654,0.0001903391,0.0002154036,0.0001499981,0.00009814544,0.0004098014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003376757,"about_ca_system_score_gemma":0.000379922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004012109,"about_ca_topic_score_gemma":0.01219127,"domain_scores_codex":[0.9996058,0.00002381331,0.00001960573,0.00003971139,0.0002732531,0.00003771949],"domain_scores_gemma":[0.9996096,0.00005107697,0.00007279398,0.00003649307,0.0002095246,0.00002046799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001450741,0.00004074367,0.01432536,0.0001197246,0.000009601362,0.0002332542,0.00009422164,0.005584005,0.9641044,0.0001273515,0.0002025435,0.01501369],"study_design_scores_gemma":[0.00002730024,0.002242008,0.3110423,0.00003837081,0.00006067102,0.001001536,0.0004802041,0.047387,0.6275067,0.0001417835,0.010033,0.00003919899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927332,0.000156137,0.005334683,0.00001335289,0.000007859402,0.00003445966,0.000214853,0.00006391968,0.001441585],"genre_scores_gemma":[0.9933313,0.00006072475,0.004548098,0.000008170899,0.000001495139,0.00001475219,0.0002530355,0.00001500875,0.001767439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004012109,"threshold_uncertainty_score":0.007977486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00922556252946677,"score_gpt":0.1893422445962106,"score_spread":0.1801166820667438,"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."}}