{"id":"W4416798782","doi":"10.1109/apsipaasc65261.2025.11249268","title":"Meta-Learning with Pretrained Audio Representations Enables One-Shot Acoustic Signal Classification","year":2025,"lang":"","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec","funders":"National Natural Science Foundation of China","keywords":"Spectrogram; Overfitting; Audio signal; Pattern recognition (psychology); SIGNAL (programming language); Hidden Markov model; Bioacoustics; Noise (video)","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","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008560995,0.0004397455,0.0006453353,0.0004132265,0.001282307,0.001381821,0.0009320189,0.0001800942,0.002177302],"category_scores_gemma":[0.0001876926,0.0003607549,0.0002159567,0.00245313,0.0003233787,0.001375636,0.0003008805,0.0005968201,0.00005297246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001176217,"about_ca_system_score_gemma":0.001149311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006437629,"about_ca_topic_score_gemma":0.00004801303,"domain_scores_codex":[0.9961235,0.0003579726,0.000778948,0.001334823,0.0007336537,0.0006711304],"domain_scores_gemma":[0.9974285,0.0005190935,0.0004787054,0.0008117331,0.000578575,0.0001834132],"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":[0.0003884194,0.002035626,0.00477538,0.002373048,0.0159869,0.000097146,0.01692631,0.2275812,0.1428742,0.2602967,0.01992105,0.3067439],"study_design_scores_gemma":[0.000976631,0.0002684903,0.004638543,0.0004027431,0.004193111,0.00001509768,0.001435174,0.9684782,0.01349338,0.003239274,0.002150383,0.0007089678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009936858,0.0009053386,0.9047862,0.008823614,0.0002109588,0.0004717946,0.000002516487,0.0002837431,0.08352216],"genre_scores_gemma":[0.8904161,0.0000635562,0.05011157,0.001493225,0.0001141194,0.0001062134,0.00001171139,0.00002091007,0.05766258],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8894224,"threshold_uncertainty_score":0.9998844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1391868398894445,"score_gpt":0.3162256056120893,"score_spread":0.1770387657226448,"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."}}