{"id":"W2559294885","doi":"10.1016/j.marpolbul.2016.11.045","title":"Geochemical assessment of heavy metals pollution in surface sediments of Vellar and Coleroon estuaries, southeast coast of India","year":2016,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Estuary; Sediment; Pollution; Enrichment factor; Organic matter; Environmental science; Environmental chemistry; Contamination; Heavy metals; Geology; Oceanography; Chemistry; Geomorphology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0000906172,0.0002616619,0.0001769235,0.00113262,0.000778606,0.0008318448,0.0003256785,0.000313985,0.0003669458],"category_scores_gemma":[0.0001326175,0.0002047859,0.0002684739,0.0009937737,0.0003984018,0.0001824466,0.0004533415,0.0001900375,0.0001225699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004217849,"about_ca_system_score_gemma":0.0006972246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06701266,"about_ca_topic_score_gemma":0.1111273,"domain_scores_codex":[0.9998971,0.000009079769,0.00001533522,0.00002444459,0.0000278202,0.00002620584],"domain_scores_gemma":[0.9998741,0.00001791431,0.00003293079,0.000006427299,0.00004997966,0.00001873851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003333545,0.00007676113,0.9294817,0.0001677094,0.00008164061,0.0009589476,0.00260042,0.0007046145,0.05540602,0.0001629761,0.0001766755,0.009849044],"study_design_scores_gemma":[0.000004809664,0.00008631349,0.9923659,0.00001024545,0.00004058799,0.0002046112,0.002348638,0.0002104243,0.004073745,0.0000332765,0.0006157786,0.00000569738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986637,0.00005792401,0.00007051729,0.00001222801,0.000001608132,0.000003995335,0.0001791163,0.000005243047,0.001005614],"genre_scores_gemma":[0.998744,0.00009091246,0.0001038374,0.00001246889,0.000001352204,0.000003999893,0.0002160572,0.00000161925,0.0008257714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06701266,"threshold_uncertainty_score":0.1332452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008060632708872325,"score_gpt":0.2283670036023711,"score_spread":0.2203063708934988,"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."}}