{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007548105,0.001377763,0.0009834639,0.0006164857,0.0003149843,0.0008321821,0.001932338,0.001031815,0.001549853],"category_scores_gemma":[0.002604455,0.0005067523,0.0009713012,0.0005111007,0.0006049302,0.001947552,0.001471247,0.002024292,0.0008924804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005439579,"about_ca_system_score_gemma":0.0006857435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002562852,"about_ca_topic_score_gemma":0.004580723,"domain_scores_codex":[0.999648,0.00005109657,0.00001608794,0.0001750425,0.00005734256,0.00005246121],"domain_scores_gemma":[0.999238,0.0002888141,0.00007642361,0.0002028181,0.0001339917,0.00005994023],"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":[0.0003240783,0.00039963,0.002964279,0.0001822395,0.0002657379,0.0002018683,0.0001504644,0.3223786,0.05337569,0.004902135,0.003697121,0.6111582],"study_design_scores_gemma":[0.000004807527,0.00006419225,0.0004279069,0.00000838119,0.00002772782,0.00003537727,0.00001642886,0.9895279,0.005757394,0.003671979,0.0004485812,0.000009291999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04069981,0.0005326986,0.9551399,0.0001796044,0.00009422113,0.0000440433,0.0001306642,0.001939071,0.001239873],"genre_scores_gemma":[0.8215898,0.0004021344,0.1728241,0.0002949842,0.0001208019,0.0001284878,0.0008114167,0.0002034336,0.00362487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002562852,"threshold_uncertainty_score":0.00518471,"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."}}