{"id":"W2153786253","doi":"","title":"PERFORMANCE OF SPECTROGRAM CROSS-CORRELATION IN DETECTING RIGHT WHALE CALLS IN LONG-TERM RECORDINGS FROM THE BERING SEA","year":2005,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spectrogram; Right whale; Computer science; Whale; Bioacoustics; Set (abstract data type); Cross-correlation; Data set; Detector; Artificial intelligence; Speech recognition; Statistics; Mathematics; Telecommunications; Fishery; Biology","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":[0.002844384,0.0004627116,0.0003820036,0.0007407619,0.0003230781,0.0005312418,0.0003542212,0.0004827202,0.0003699035],"category_scores_gemma":[0.009929342,0.0002634208,0.0002093437,0.0004429551,0.0002835077,0.0005383888,0.0004303246,0.0002401244,0.0002600674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000338213,"about_ca_system_score_gemma":0.0004538992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008090871,"about_ca_topic_score_gemma":0.01672388,"domain_scores_codex":[0.9988441,0.0003640944,0.00005327777,0.0003130072,0.0003247115,0.0001007467],"domain_scores_gemma":[0.9919951,0.005098299,0.0005857313,0.0003976385,0.001643149,0.0002800719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002675038,0.0003406634,0.3958336,0.0002933987,0.0004238919,0.0005000282,0.002173458,0.02994937,0.2562609,0.0002755106,0.001025631,0.3102486],"study_design_scores_gemma":[0.00004892179,0.001125861,0.7182999,0.00002265682,0.0001601471,0.0006608374,0.0003252053,0.2200388,0.05823154,0.000100314,0.0008917472,0.00009414808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895679,0.0001528993,0.009532818,0.00002437756,0.000008983994,0.00001043914,0.00004374153,0.0001720071,0.0004867995],"genre_scores_gemma":[0.9855606,0.0000786672,0.01371007,0.00001926444,0.00001050068,0.00001286259,0.0001849259,0.00004023184,0.0003830299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008090871,"threshold_uncertainty_score":0.01608759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008798937553840794,"score_gpt":0.2237925292875625,"score_spread":0.2149935917337218,"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."}}