{"id":"W2281243816","doi":"10.1299/jsmehs.2008.45.401","title":"1118 Defect Detection of Rolling Guides Using Vibration and AE signals : Defects of Bearing Blocks","year":2008,"lang":"en","type":"article","venue":"The Proceedings of Conference of Hokuriku-Shinetsu Branch","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"MD Precision (Canada)","funders":"","keywords":"Bearing (navigation); Vibration; Structural engineering; Materials science; Acoustics; Computer science; Engineering; Physics; Artificial intelligence","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":[0.0001888272,0.0002947258,0.0002690771,0.0008469925,0.0001197896,0.0002200205,0.0002892728,0.0005729918,0.001586358],"category_scores_gemma":[0.0005868322,0.0002078498,0.0001186202,0.0003005963,0.0002554807,0.0003664606,0.0001913249,0.0002122412,0.0003132937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008054847,"about_ca_system_score_gemma":0.000123277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005225901,"about_ca_topic_score_gemma":0.000757254,"domain_scores_codex":[0.9998192,0.00002143002,0.000007759884,0.00003550578,0.00008838388,0.00002765911],"domain_scores_gemma":[0.9993819,0.0001724999,0.00008503705,0.00004670483,0.0002444283,0.00006929833],"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":[0.0008457519,0.00006828846,0.01749246,0.00008163648,0.00002093252,0.0004546865,0.0001616074,0.001716076,0.9320976,0.0002071843,0.000574953,0.04627882],"study_design_scores_gemma":[0.00006207269,0.001203283,0.1538185,0.00002069355,0.0001022984,0.002436962,0.0005047632,0.1329436,0.7051846,0.0002550488,0.003408915,0.00005920199],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765828,0.0001343252,0.02209821,0.00003372598,0.00002270067,0.000007920225,0.00005447281,0.0001542998,0.0009114938],"genre_scores_gemma":[0.9930374,0.0000296293,0.005928928,0.00000837667,0.000006030555,0.000003170517,0.00005993463,0.00001526783,0.0009113087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001586358,"threshold_uncertainty_score":0.00530684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03044530995222864,"score_gpt":0.2158753678675643,"score_spread":0.1854300579153356,"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."}}