{"id":"W2793919535","doi":"10.1002/ecs2.2127","title":"Integrating multiple disciplines to understand effects of anthropogenic noise on animal communication","year":2018,"lang":"en","type":"article","venue":"Ecosphere","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Fish and Wildlife Service; Research Manitoba; University of Manitoba; Cenovus Energy","keywords":"Psychoacoustics; Multidisciplinary approach; Noise (video); Perception; Computer science; Animal communication; Soundscape; Ecology; Data science; Psychology; Artificial intelligence; Biology; Acoustics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007428045,0.00009831548,0.0001008891,0.00001144822,0.0001312175,0.00001218133,0.0002738257,0.0000725525,0.00008180863],"category_scores_gemma":[0.0001424423,0.000085007,0.00005294369,0.00008440091,0.0001319382,0.000003532777,0.000195059,0.00006739422,0.00006642682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001510017,"about_ca_system_score_gemma":0.00002137157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000320995,"about_ca_topic_score_gemma":0.0007497898,"domain_scores_codex":[0.999441,0.00006312304,0.00015361,0.0001610121,0.00007032802,0.0001109376],"domain_scores_gemma":[0.9992259,0.00003886173,0.00006836419,0.0005160063,0.00009539662,0.00005546332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002378596,0.0001678618,0.002253581,0.00001780092,0.00001627791,2.687425e-7,0.0002736467,0.000003215477,0.9887802,0.0003680266,0.004663644,0.003217641],"study_design_scores_gemma":[0.0005405421,0.002400693,0.04659657,0.00009211997,0.00001824658,0.000001398243,0.001170443,0.0001545582,0.9451715,0.0000474486,0.00361973,0.0001867143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947422,0.0002553073,0.00124449,0.0002293477,0.00004307223,0.0001919154,0.000006634209,0.00001242215,0.00327462],"genre_scores_gemma":[0.9958231,0.00004606466,0.003589133,0.0001535845,0.00006477399,0.000009053063,0.0000324036,0.00001512233,0.0002667948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04434299,"threshold_uncertainty_score":0.3466485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694198728079795,"score_gpt":0.3054830545352505,"score_spread":0.2885410672544526,"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."}}