{"id":"W2965503177","doi":"10.1038/s41598-019-47335-w","title":"ORCA-SPOT: An Automatic Killer Whale Sound Detection Toolkit Using Deep Learning","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Paul G. Allen Frontiers Group; University of Victoria","keywords":"Bioacoustics; Whale; Computer science; Noise (video); Deep learning; Artificial intelligence; Scale (ratio); Pattern recognition (psychology); Biology; Ecology; Cartography; Geography; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001410064,0.000178152,0.0002119751,0.00006138239,0.0006693503,0.0003305513,0.0001746936,0.00006237555,0.01002516],"category_scores_gemma":[0.0001318286,0.0001641469,0.00008536565,0.0005830915,0.0001939301,0.000735253,0.0004297736,0.0001628447,0.001298835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002963334,"about_ca_system_score_gemma":0.00001461456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008448411,"about_ca_topic_score_gemma":0.001556698,"domain_scores_codex":[0.9974705,0.0000855417,0.0004240239,0.0008887705,0.000704011,0.0004271633],"domain_scores_gemma":[0.9988175,0.0000255946,0.0003082935,0.0006925811,0.00002647073,0.0001295664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001130988,0.0002030626,0.6982698,0.0001159552,0.00004170748,0.0002628406,0.001892673,0.02578121,0.08856503,0.00001519944,0.0008706935,0.1839705],"study_design_scores_gemma":[0.0004666825,0.0003906641,0.4903908,0.0001183839,0.0001274262,0.001309776,0.001388927,0.2205804,0.007667751,0.004679572,0.2713106,0.001569036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983524,0.00006442175,0.0003040808,0.00001047497,0.003383155,0.0003430424,1.045217e-7,0.0001304278,0.01224024],"genre_scores_gemma":[0.9915892,0.000003204264,0.0008864469,0.0000321181,0.00004050783,0.000009622737,0.000005457306,0.00002229209,0.007411181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2704399,"threshold_uncertainty_score":0.9994788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844029044544022,"score_gpt":0.2439940842687384,"score_spread":0.2255537938232982,"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."}}