{"id":"W3005719954","doi":"10.4236/gep.2020.82007","title":"Evaluation of the Level of Mercury Pollution in the Sediments of the Rivers Draining the Gold Panning Sites in the Territory of Fizi, Eastern Democratic Republic of Congo","year":2020,"lang":"en","type":"article","venue":"Journal of Geoscience and Environment Protection","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Pollution; Environmental chemistry; Environmental science; Mercury pollution; Gold mining; Contamination; Dry season; Chemistry; Ecology; Biology","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":[0.0002033907,0.0002761037,0.0002223805,0.001218188,0.0005774295,0.0006664111,0.0001750879,0.0002990137,0.0003687785],"category_scores_gemma":[0.0003023827,0.0001788405,0.0001918514,0.001480966,0.0004271666,0.0002601257,0.0003268995,0.0001705715,0.0000612548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000661468,"about_ca_system_score_gemma":0.0004396797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03168697,"about_ca_topic_score_gemma":0.09215089,"domain_scores_codex":[0.9998647,0.00001677479,0.00002071915,0.00003792271,0.00003480173,0.00002506075],"domain_scores_gemma":[0.999853,0.00001468582,0.00007264219,0.00000714167,0.00003840539,0.00001411524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001476402,0.00003452042,0.9470165,0.00009802194,0.0001118591,0.0007976476,0.002325518,0.0003591421,0.04203655,0.00009897028,0.00004587659,0.006927882],"study_design_scores_gemma":[0.000001002564,0.00002448484,0.9974706,0.000004456424,0.00001860994,0.0001215413,0.0005837168,0.00009028314,0.001401467,0.000007695921,0.0002727282,0.000003423601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994096,0.00007754557,0.00004696062,0.000006660508,6.207018e-7,0.000003399111,0.00009666019,0.000001430196,0.0003573429],"genre_scores_gemma":[0.9990919,0.0001291511,0.0002091305,0.000006286855,0.000001695699,0.00000744924,0.0001433977,9.793667e-7,0.0004100356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03168697,"threshold_uncertainty_score":0.06300503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1274934801969327,"score_gpt":0.2830763703826049,"score_spread":0.1555828901856721,"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."}}