{"id":"W2944806726","doi":"10.1016/j.ecoinf.2019.05.007","title":"Handcrafted features and late fusion with deep learning for bird sound classification","year":2019,"lang":"en","type":"article","venue":"Ecological Informatics","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Fundamental Research Funds for the Central Universities; Higher Education Discipline Innovation Project","keywords":"Artificial intelligence; Deep learning; Computer science; Pattern recognition (psychology); Convolutional neural network; Machine learning","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":[0.0006130344,0.0008753064,0.0008632866,0.0007479149,0.0002992461,0.0007254052,0.0009798043,0.0009366134,0.002881277],"category_scores_gemma":[0.001152803,0.0003553675,0.0007060273,0.0009063908,0.0003062802,0.001041065,0.001373478,0.00156818,0.001505837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003730881,"about_ca_system_score_gemma":0.0006751518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004180961,"about_ca_topic_score_gemma":0.005773148,"domain_scores_codex":[0.9996965,0.00004068419,0.00001756818,0.00008719523,0.00008046725,0.00007769191],"domain_scores_gemma":[0.9995783,0.00012646,0.00003762134,0.00009103485,0.0001323802,0.00003416862],"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":[0.0004678546,0.0002822217,0.002636451,0.00008911058,0.0001048886,0.00008495453,0.00005987557,0.07839578,0.03797213,0.002463222,0.007882543,0.8695609],"study_design_scores_gemma":[0.00001020074,0.00006684165,0.001194331,0.000008630824,0.00002209763,0.0000298648,0.00001498932,0.987561,0.007804181,0.002210797,0.001065952,0.00001102008],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08208618,0.001101737,0.9093711,0.0002750447,0.0002330693,0.00005419253,0.0006654921,0.004464166,0.001749084],"genre_scores_gemma":[0.7170314,0.0004220589,0.2708961,0.0001961901,0.0001558378,0.000102494,0.002358965,0.0002532444,0.008583701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004180961,"threshold_uncertainty_score":0.009638846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02262859165402929,"score_gpt":0.2723322040277495,"score_spread":0.2497036123737202,"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."}}