{"id":"W1607089241","doi":"","title":"Bias in Estimates of Numbers of Marine Mammals Affected by Underwater Noise","year":2010,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Underwater; Noise (video); Underwater acoustics; Acoustics; Underwater acoustic communication; Environmental science; Marine engineering; Computer science; Geology; Oceanography; Engineering; Physics; Artificial intelligence","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":[0.009584352,0.0005033658,0.0005265097,0.004054351,0.001113632,0.001477828,0.001493572,0.0005303574,0.001435255],"category_scores_gemma":[0.02624019,0.0003692454,0.0004644919,0.005316826,0.001494768,0.0008862165,0.001094282,0.0005754481,0.0002543149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008638307,"about_ca_system_score_gemma":0.007981642,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.938055,"about_ca_topic_score_gemma":0.9681875,"domain_scores_codex":[0.9929339,0.001148695,0.0005117088,0.001137054,0.003808332,0.0004603239],"domain_scores_gemma":[0.9743006,0.005227244,0.002984737,0.001096348,0.0158542,0.0005368737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002064765,0.00001087744,0.8936772,0.0006977874,0.0006829086,0.00008198823,0.002545317,0.002009681,0.001300963,0.001806993,0.009074344,0.08790551],"study_design_scores_gemma":[0.000005696172,0.00001980166,0.9860994,0.0002675337,0.0002068413,0.0001123545,0.001051883,0.0004560464,0.0005157168,0.0004280141,0.01080629,0.00003052178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7621168,0.09631959,0.02323469,0.007278149,0.001161376,0.0002118815,0.02563413,0.0003828299,0.08366055],"genre_scores_gemma":[0.9590601,0.02011095,0.009415442,0.001431901,0.0003106272,0.00005645964,0.005274701,0.00008236904,0.004257489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.938055,"threshold_uncertainty_score":0.1246195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267545430069384,"score_gpt":0.2219777939432367,"score_spread":0.2093023396425429,"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."}}