{"id":"W2550937321","doi":"10.1016/j.marpolbul.2016.11.021","title":"Fractionation of heavy metals in sediments and assessment of their availability risk: A case study in the northwestern of Persian Gulf","year":2016,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; University of Tehran","keywords":"Fractionation; Carbonate; Environmental chemistry; Extraction (chemistry); Contamination; Environmental science; Nickel; Heavy metals; Chemistry; Chromatography; Ecology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002075062,0.0001140129,0.0002284157,0.00007684802,0.00003293118,0.000003072742,0.0001267681,0.00004082534,0.00153687],"category_scores_gemma":[0.00006711529,0.00007054962,0.0000411803,0.0001652865,0.0002427048,0.00006753815,0.0002410712,0.0001022588,0.000007587558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731587,"about_ca_system_score_gemma":0.000009759069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01041742,"about_ca_topic_score_gemma":0.00309667,"domain_scores_codex":[0.9980204,0.0006704009,0.0005490105,0.0002533698,0.0003734885,0.0001333973],"domain_scores_gemma":[0.9991348,0.0002005629,0.0002963009,0.0003325737,0.000005683611,0.00003007603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003067461,0.001088949,0.9823976,0.000008627924,0.00001374268,0.00001040227,0.00125144,0.0002998282,0.001664593,0.000007955531,0.00001083571,0.01321538],"study_design_scores_gemma":[0.0009154317,0.0002262741,0.994319,0.00001112908,0.00001705128,0.00002305311,0.002453218,0.0001430332,0.001066084,0.00007400494,0.0006851492,0.00006653971],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973965,0.00001016231,0.0002231109,0.0009451602,0.00002723862,0.0006325377,0.00002735786,0.000002957351,0.0007350044],"genre_scores_gemma":[0.9991206,0.00003243457,0.0007057756,0.0000293154,0.000004461944,0.00003857837,0.000001487946,0.000005674334,0.00006166039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01314884,"threshold_uncertainty_score":0.9993759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684116142718715,"score_gpt":0.2706136338261967,"score_spread":0.2537724723990096,"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."}}