{"id":"W4411263732","doi":"10.1016/j.eswa.2025.128601","title":"A novel method based on wavelet transform and prototypical network for gearbox detection in few-shot learning","year":2025,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Gear and Bearing Dynamics Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Manitoba","funders":"Tsinghua University","keywords":"Computer science; Artificial intelligence; Shot (pellet); Wavelet transform; Pattern recognition (psychology); Wavelet; Machine learning; Continuous wavelet transform; Discrete wavelet transform; Materials science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001971275,0.0001069342,0.000169558,0.0001270054,0.000111626,0.00004027376,0.00005428383,0.00007480015,9.521069e-7],"category_scores_gemma":[0.000007354554,0.00009414407,0.00003391311,0.0003921069,0.00001043649,0.00001837786,0.00000376045,0.000139733,9.293599e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006760386,"about_ca_system_score_gemma":0.00001501325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001845215,"about_ca_topic_score_gemma":0.0002374994,"domain_scores_codex":[0.9993874,0.00001567276,0.000171197,0.0001929944,0.00006949769,0.0001632255],"domain_scores_gemma":[0.999657,0.0001191648,0.00001863817,0.0001428924,0.00002781478,0.00003450049],"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":[0.00005984803,0.00005453344,0.0003430423,0.0002168245,0.00006483452,1.892233e-7,0.0001369655,0.9716904,0.004945038,0.003476155,0.00002233676,0.01898979],"study_design_scores_gemma":[0.0003858447,0.00004195029,0.0005736207,0.0000961371,0.00001596202,0.000001796714,0.00007264354,0.9845468,0.0002496348,0.00003570431,0.01387493,0.0001049204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009248158,0.00008457879,0.9960865,0.000108258,0.00002388647,0.001621249,0.000003910891,0.0001084213,0.001038349],"genre_scores_gemma":[0.9595137,0.00000522224,0.03247929,0.000028318,0.00005337333,0.007765667,0.00001425834,0.00002230414,0.000117897],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9636073,"threshold_uncertainty_score":0.3839084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009449258409089792,"score_gpt":0.255898810586471,"score_spread":0.2464495521773812,"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."}}