{"id":"W2959222730","doi":"10.1016/j.scitotenv.2019.07.147","title":"Tropical seabirds sample broadscale patterns of marine contaminants","year":2019,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Society for Integrative and Comparative Biology; U.S. Fish and Wildlife Service; Nature Conservancy; Society for Integrative and Comparative Biology (SICB); Sigma Xia; U.S. Environmental Protection Agency","keywords":"Seabird; Foraging; Tern; Tropical marine climate; Mercury (programming language); Range (aeronautics); Environmental science; Ecology; Marine pollution; Contamination; Biomonitoring; Charadriiformes; Biology; Predation; Pollution","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":[0.0001545668,0.0002222794,0.0001912727,0.0006387679,0.0003766478,0.0005047613,0.0001428151,0.0002153443,0.002360041],"category_scores_gemma":[0.0003753783,0.0001862521,0.0002050126,0.0008142308,0.0003051801,0.0002851504,0.0003232833,0.0002479964,0.0004294532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002200744,"about_ca_system_score_gemma":0.0001820485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0233008,"about_ca_topic_score_gemma":0.06709376,"domain_scores_codex":[0.999841,0.00002924971,0.000006277101,0.00006034284,0.00001924587,0.00004391115],"domain_scores_gemma":[0.9996196,0.00005091927,0.0001579238,0.00004726986,0.00005580815,0.00006847357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001256296,0.0000419303,0.9808586,0.00001501936,0.0001377108,0.00002720376,0.0002883195,0.00009002924,0.01332405,0.00002627772,0.0001827455,0.004882418],"study_design_scores_gemma":[8.462991e-7,0.00001575203,0.999332,0.000001045007,0.000009154878,0.0000239734,0.0002173746,0.00001697027,0.0002221303,0.000006359288,0.0001534523,8.130098e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984885,0.00009315238,0.0001232142,0.00001484631,0.000002786091,0.000004531503,0.000554483,0.000004643905,0.0007138185],"genre_scores_gemma":[0.9980081,0.0001483932,0.0002518874,0.00006561589,0.000005104693,0.000008726885,0.0008212936,0.000009918778,0.0006810195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0233008,"threshold_uncertainty_score":0.04633033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065257874693959,"score_gpt":0.224487184692703,"score_spread":0.2138346059457634,"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."}}