{"id":"W2134641446","doi":"","title":"Feature-Aided Tracking for Marine Mammal Detection and Classification","year":2008,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Naval Undersea Warfare Center; Ocean Life Institute, Woods Hole Oceanographic Institution; Woods Hole Oceanographic Institution","keywords":"Beaked whale; Human echolocation; Computer science; Whale; Bioacoustics; Marine mammal; Feature (linguistics); Artificial intelligence; Sperm whale; Tracking (education); Pattern recognition (psychology); Speech recognition; Acoustics; Biology; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000694374,0.00008603284,0.00008401198,0.00002740589,0.000307322,0.00001514499,0.00006819222,0.0000592195,0.0001783238],"category_scores_gemma":[0.0001011004,0.00009082826,0.00002130698,0.0001050675,0.00008836445,0.00007190298,0.00004812574,0.00007440874,0.00003695059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003360155,"about_ca_system_score_gemma":0.00002281357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02731113,"about_ca_topic_score_gemma":0.2622022,"domain_scores_codex":[0.9994183,0.000008321555,0.00007599626,0.0001834655,0.00008237085,0.0002316063],"domain_scores_gemma":[0.9996351,0.0000300626,0.00003474797,0.0001002004,0.00001333032,0.0001865505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000461854,0.00002988686,0.3337446,0.0000930745,0.00003581284,0.00005872337,0.0003434476,0.0002878509,0.05003431,0.0002938635,0.05379993,0.5612323],"study_design_scores_gemma":[0.0001397328,0.00004037994,0.9382839,0.000002118582,0.00001734752,0.00003186657,0.00002961607,0.006069676,0.0000635301,0.00008259739,0.0551299,0.0001093214],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981003,0.00005923896,0.00358063,0.0008075871,0.0001518103,0.0004126596,0.00002453042,0.00003317508,0.01392738],"genre_scores_gemma":[0.9957672,0.000135541,0.002140709,0.0004245959,0.00007383214,0.00002072235,0.000007527942,0.00001270098,0.001417187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6045393,"threshold_uncertainty_score":0.9791661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03071337677351848,"score_gpt":0.2233408601937946,"score_spread":0.1926274834202761,"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."}}