{"id":"W4378695344","doi":"10.1007/978-3-031-10417-6_22-1","title":"Interference of Communication and Echolocation of Southern Resident Killer Whales","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Human echolocation; Disturbance (geology); Marine mammal; Ambient noise level; Range (aeronautics); Noise (video); Metric (unit); Interference (communication); Masking (illustration); Ecology; Noise pollution; Environmental science; Computer science; Geography; Sound (geography); Noise reduction; Environmental resource management; Acoustics; Biology; Engineering; Telecommunications; Artificial intelligence","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":[0.0001624716,0.0002613971,0.0001740124,0.0004037407,0.0003176829,0.0008147139,0.0003348029,0.0003255606,0.008942712],"category_scores_gemma":[0.000148608,0.0001184645,0.00012233,0.0005828739,0.000390219,0.0004594375,0.0005980172,0.000334898,0.00131081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003225816,"about_ca_system_score_gemma":0.0002619722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005084273,"about_ca_topic_score_gemma":0.01084949,"domain_scores_codex":[0.9999378,0.00001130004,0.000002208926,0.00001026001,0.00002740725,0.00001099402],"domain_scores_gemma":[0.9999422,0.00003198367,0.000006635083,0.000002968927,0.00001128415,0.000004829525],"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":[0.0001647313,0.0001036693,0.004444444,0.0008270624,0.00003909925,0.001218784,0.00315785,0.0008241562,0.05253626,0.05427348,0.03724131,0.8451691],"study_design_scores_gemma":[0.000008846885,0.0003352437,0.05016407,0.000428937,0.0000425176,0.002314035,0.002719183,0.000520681,0.009046177,0.01158523,0.9228149,0.00002024218],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09134675,0.193527,0.006517688,0.003012379,0.001129021,0.00003503881,0.0001872246,0.0001025809,0.7041424],"genre_scores_gemma":[0.1431798,0.0972933,0.002383945,0.0007710761,0.0007984242,0.00004753636,0.0002783045,0.00005939995,0.7551883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008942712,"threshold_uncertainty_score":0.02991641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216651120494973,"score_gpt":0.2480690466107787,"score_spread":0.205902535405829,"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."}}