{"id":"W1590707944","doi":"","title":"A comparison of pitch extraction methodologies for dolphin vocalization","year":2008,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Speech recognition; Hidden Markov model; Mel-frequency cepstrum; Autocorrelation; Fundamental frequency; Acoustics; Harmonic; Noise (video); Range (aeronautics); Bioacoustics; Artificial intelligence; Pattern recognition (psychology); Feature extraction; Mathematics; Engineering; Physics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001989736,0.001208409,0.0008176044,0.002918893,0.0004403434,0.001046966,0.0009832747,0.001102955,0.002174152],"category_scores_gemma":[0.004408136,0.0004220606,0.000874561,0.001513249,0.0002651916,0.001426294,0.0007666182,0.0006388227,0.001444012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003410898,"about_ca_system_score_gemma":0.0005988814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003036325,"about_ca_topic_score_gemma":0.003835268,"domain_scores_codex":[0.9983588,0.0002556878,0.0001565457,0.0004762051,0.0006323037,0.0001205243],"domain_scores_gemma":[0.9980839,0.000904783,0.0001474302,0.0001628265,0.000623069,0.00007798032],"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":[0.0009170547,0.0001561634,0.008493823,0.0008026038,0.0002984696,0.0001367698,0.000328961,0.01235314,0.06874771,0.0007704548,0.002242398,0.9047525],"study_design_scores_gemma":[0.0003039794,0.002404074,0.09961268,0.0004422232,0.000712436,0.002766027,0.001396619,0.6149516,0.2426843,0.002563905,0.03179371,0.0003683961],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2427702,0.009365246,0.731802,0.0002536531,0.0004153078,0.0003429907,0.001172408,0.008844612,0.005033691],"genre_scores_gemma":[0.2640946,0.004580994,0.721757,0.0001482102,0.000127819,0.0001902849,0.00371081,0.0007207592,0.00466944],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003036325,"threshold_uncertainty_score":0.01052284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1491084012886626,"score_gpt":0.3704253371494866,"score_spread":0.2213169358608239,"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."}}