{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008159979,0.0006707934,0.0009617973,0.0008995814,0.0002855225,0.000729145,0.0006918056,0.0007667325,0.002895368],"category_scores_gemma":[0.002306069,0.0002231332,0.0006775015,0.0009161282,0.000318193,0.0006840915,0.0008373561,0.0009258678,0.002165464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002991149,"about_ca_system_score_gemma":0.0005995898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002304053,"about_ca_topic_score_gemma":0.002027702,"domain_scores_codex":[0.9994554,0.0001457004,0.00002906689,0.000147129,0.000137212,0.00008551183],"domain_scores_gemma":[0.9989302,0.0004411935,0.00006373179,0.000243898,0.0002823673,0.00003866612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003062657,0.0001441705,0.001457183,0.000105874,0.00004389646,0.00008928509,0.00006358454,0.09278488,0.05495105,0.00134181,0.006782413,0.8419296],"study_design_scores_gemma":[0.00001323808,0.00005281021,0.00156404,0.000007539328,0.00001599308,0.00009349551,0.00003577951,0.9749638,0.01686525,0.003535714,0.002842173,0.00001026932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05090711,0.0006538749,0.9415509,0.0002393161,0.0001254407,0.00005521199,0.0003564324,0.004607953,0.001503671],"genre_scores_gemma":[0.6594982,0.0006453525,0.3302248,0.0002206916,0.0001698358,0.0001339701,0.002115285,0.0003804234,0.006611511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002895368,"threshold_uncertainty_score":0.009685934,"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."}}