{"id":"W2082530523","doi":"10.1016/j.envpol.2011.01.024","title":"Analyzing trophic transfer of heavy metals for food webs in the newly-formed wetlands of the Yellow River Delta, China","year":2011,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":223,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China; National Research Foundation; Scientific Research Foundation of Beijing Normal University; National Science Foundation","keywords":"Wetland; Trophic level; Delta; China; Food chain; River delta; Heavy metals; Environmental science; Ecology; Geography; Biology; Environmental chemistry; Chemistry; Archaeology","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":[0.0003725903,0.0003571151,0.0003745847,0.001161773,0.0009670643,0.0005297705,0.0004059302,0.0002888985,0.0003388148],"category_scores_gemma":[0.0004076469,0.000303991,0.0003927849,0.0008328545,0.000562796,0.0005022651,0.000716289,0.000196393,0.00005132677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001849485,"about_ca_system_score_gemma":0.001226252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08787072,"about_ca_topic_score_gemma":0.1619172,"domain_scores_codex":[0.999843,0.00002232151,0.000009211945,0.00004652096,0.00002944507,0.00004947448],"domain_scores_gemma":[0.9997446,0.00004827795,0.0000539566,0.00002040168,0.00006303698,0.00006969975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000125532,0.00004818091,0.9697403,0.00002144028,0.0000931534,0.000186917,0.001135533,0.0007866211,0.02422095,0.0001140492,0.00004007177,0.003487126],"study_design_scores_gemma":[0.000002920295,0.0000161842,0.997752,0.00000111572,0.00001438563,0.00002551256,0.0004006692,0.001298993,0.0004060186,0.00003094607,0.00004720765,0.000004027806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9999187,0.000005768859,0.00002644055,0.000001933638,1.866385e-7,6.527308e-7,0.00001207662,5.54732e-7,0.00003358698],"genre_scores_gemma":[0.9997703,0.000009962803,0.00006397186,0.000002501341,4.122813e-7,0.000002315007,0.00004606398,6.549746e-7,0.0001038465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08787072,"threshold_uncertainty_score":0.1747185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181429656162414,"score_gpt":0.2085811487064559,"score_spread":0.1904381830902145,"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."}}