{"id":"W2188390241","doi":"10.1021/acs.est.5b03978","title":"PCB Food Web Dynamics Quantify Nutrient and Energy Flow in Aquatic Ecosystems","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Nutrient; Food web; Environmental science; Trophic level; Energy flow; Ecosystem; Aquatic ecosystem; Ecology; Trout; Nutrient cycle; Food chain; Trophic state index; Bioaccumulation; Eutrophication; Biology; Fish <Actinopterygii>; Fishery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002763984,0.0002271133,0.0002204478,0.001277728,0.0002822501,0.0005181113,0.0002042131,0.00027019,0.0009385066],"category_scores_gemma":[0.0005553754,0.0001928469,0.0001461221,0.0009905139,0.0002747314,0.0006582622,0.0004698,0.0002098391,0.0002109343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009334396,"about_ca_system_score_gemma":0.0003633488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01197507,"about_ca_topic_score_gemma":0.03054382,"domain_scores_codex":[0.9998544,0.00001836324,0.000008578971,0.00004532268,0.00005704772,0.00001611752],"domain_scores_gemma":[0.9996718,0.00006151765,0.0001503682,0.00001924896,0.00007343752,0.00002358032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001376707,0.00006017946,0.7059796,0.0001801219,0.0002147717,0.00007334559,0.0002842391,0.006748637,0.2539313,0.0007559596,0.0003501026,0.03128422],"study_design_scores_gemma":[0.000004443761,0.00007707854,0.9708572,0.00001032918,0.00003470814,0.00007583942,0.0001310744,0.01052465,0.01677462,0.0006238824,0.0008717903,0.00001425547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887001,0.0004913259,0.007682993,0.0000471401,0.000003440816,0.00002344108,0.001198992,0.00007669354,0.001775989],"genre_scores_gemma":[0.9915945,0.0003853521,0.006551608,0.00003597349,0.000003686363,0.00002914979,0.000623126,0.00002462081,0.0007519923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01197507,"threshold_uncertainty_score":0.02381074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006791418768966624,"score_gpt":0.2003937245683083,"score_spread":0.1936023057993417,"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."}}