{"id":"W6981635093","doi":"","title":"Estimates of heavy metals pollution in parishan wetland sediments using pollution indices","year":2017,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pollution; Contamination; Sediment; Wetland; Pollutant; Heavy metals; Zinc","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002016117,0.000442941,0.0001805618,0.001774129,0.0001842285,0.0004476443,0.0001831703,0.0001690832,0.0004408842],"category_scores_gemma":[0.0001867446,0.0001192126,0.000195701,0.001177131,0.0002200199,0.0001867804,0.0003281857,0.0001172724,0.0001167045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003188866,"about_ca_system_score_gemma":0.0003076891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004691866,"about_ca_topic_score_gemma":0.009430626,"domain_scores_codex":[0.9998227,0.00001576106,0.00001391839,0.00004509305,0.00008741773,0.00001520256],"domain_scores_gemma":[0.9998559,0.00001588317,0.00006624044,0.000008758398,0.00004415491,0.000009092497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002011631,0.00008856339,0.7762892,0.0004316645,0.0002758764,0.0006338325,0.000630948,0.004105768,0.1508087,0.0002548742,0.0004642645,0.06581511],"study_design_scores_gemma":[0.000005426733,0.0001659843,0.9611771,0.00002026456,0.00009300219,0.000406325,0.0003940462,0.00308169,0.0321188,0.0001568365,0.002356389,0.00002409177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935777,0.0004220307,0.003098117,0.00001317192,0.000004310511,0.00003054721,0.0004804817,0.00005361646,0.002320058],"genre_scores_gemma":[0.9933635,0.0002804082,0.004904929,0.000008483759,0.000004183999,0.00002872108,0.0004677507,0.000004642248,0.0009374582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004691866,"threshold_uncertainty_score":0.00932914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2388362930402577,"score_gpt":0.533420459875277,"score_spread":0.2945841668350193,"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."}}