{"id":"W4384751970","doi":"","title":"Automated domain adaptation for bearings fault detection and classification","year":2023,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"European Commission","keywords":"Domain adaptation; Computer science; Adaptation (eye); Fault detection and isolation; Domain (mathematical analysis); Fault (geology); Artificial intelligence; Pattern recognition (psychology); Geology; Actuator; Seismology; Psychology; Classifier (UML); Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005848566,0.0005652815,0.0005183161,0.0004255924,0.000496677,0.0005309301,0.0006882992,0.0007310854,0.00002664407],"category_scores_gemma":[0.002234626,0.0007186706,0.0002280293,0.000567561,0.0002197116,0.0003046004,0.0005287631,0.0007357569,0.00007884227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004845072,"about_ca_system_score_gemma":0.0001116614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003448157,"about_ca_topic_score_gemma":0.00659951,"domain_scores_codex":[0.9947667,0.002328627,0.0009071822,0.001067918,0.0004022565,0.0005273899],"domain_scores_gemma":[0.993393,0.0026439,0.0005549325,0.001447164,0.001737252,0.0002237462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000738326,0.0009628299,0.005800691,0.003655678,0.0005881391,0.000008198712,0.03554145,0.009292896,0.1802376,0.3598547,0.004976049,0.3990079],"study_design_scores_gemma":[0.0005880475,0.000001380256,0.05162129,0.00184928,0.0001007352,0.00001014834,0.000233476,0.8636472,0.05062588,0.01435138,0.01634486,0.0006263849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1415293,0.0005940745,0.8365705,0.009797986,0.0005249555,0.001870011,0.0001922578,0.004902625,0.004018298],"genre_scores_gemma":[0.7065842,0.001542807,0.2855833,0.00002663476,0.00005732733,0.001323952,0.00109763,0.0002013286,0.003582818],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8543543,"threshold_uncertainty_score":0.9995264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387609060375395,"score_gpt":0.2658519349723846,"score_spread":0.2419758443686307,"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."}}