{"id":"W2751302219","doi":"10.1016/j.marpolbul.2017.08.002","title":"Effects of shipping on marine acoustic habitats in Canadian Arctic estimated via probabilistic modeling and mapping","year":2017,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Rimouski; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Arctic; Noise (video); Probabilistic logic; Environmental science; Marine spatial planning; Habitat; Subarctic climate; Ambient noise level; Physical geography; Meteorology; Geography; Oceanography; Computer science; Ecology; Environmental resource management; Sound (geography); Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004104256,0.0002150868,0.0002974268,0.0001050721,0.0003543024,0.00004674902,0.0002531366,0.00006700514,0.0008699086],"category_scores_gemma":[0.001247297,0.0002180301,0.00003821426,0.0001171885,0.0001794057,0.00006279613,0.0009801261,0.0001896313,0.0001160457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000626013,"about_ca_system_score_gemma":0.00002301921,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.74283,"about_ca_topic_score_gemma":0.5870652,"domain_scores_codex":[0.9985044,0.00006206337,0.0003240508,0.0003987299,0.0002132193,0.0004975089],"domain_scores_gemma":[0.9992307,0.00008407058,0.0001510806,0.0003243489,0.00001770403,0.0001920758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001059949,0.0001860803,0.8575309,0.00113685,0.00003808898,0.0001280556,0.000199613,0.03861211,0.001025392,0.0005329675,0.0001692313,0.1003347],"study_design_scores_gemma":[0.0004684382,0.00006857746,0.813666,0.0001906977,0.00001912063,0.000006916272,0.000007170597,0.1839474,0.00001950059,0.0008957529,0.0005205161,0.0001898484],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869069,0.00004166434,0.0002425924,0.002453656,0.0000920344,0.0006069675,0.000002572557,0.00002795103,0.009625605],"genre_scores_gemma":[0.9984824,0.00005561945,0.0009449435,0.0002592974,0.00002158214,0.00004150949,0.000003945556,0.00001950582,0.0001711712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1557648,"threshold_uncertainty_score":0.9524889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01817073512004173,"score_gpt":0.2327063535904335,"score_spread":0.2145356184703918,"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."}}