{"id":"W2594248856","doi":"10.1038/srep42198","title":"Arsenic Methylation and its Relationship to Abundance and Diversity of arsM Genes in Composting Manure","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Science and Technology Department of Zhejiang Province; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Manure; Methylation; Compost; Chicken manure; Abundance (ecology); Biology; Relative species abundance; Food science; Arsenic; Streptomyces; Gene; Microbiology; Bacteria; Chemistry; Agronomy; Genetics; Ecology","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":[0.0001533146,0.0002060119,0.000252062,0.0006491953,0.0001170298,0.0003145804,0.0001035229,0.0002160536,0.0003992207],"category_scores_gemma":[0.0003005731,0.0001475845,0.0001756124,0.0004768939,0.0002030551,0.000156526,0.0001958729,0.0001852436,0.0001086083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000112681,"about_ca_system_score_gemma":0.0001228338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007561579,"about_ca_topic_score_gemma":0.0006431181,"domain_scores_codex":[0.9998232,0.00002629337,0.00001533924,0.00005095179,0.00004182678,0.00004243003],"domain_scores_gemma":[0.999765,0.00004753787,0.00008592929,0.000012625,0.00005008518,0.00003886664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001652898,0.00001832232,0.009816567,0.00002369681,0.000006989375,0.00003316713,0.00003823641,0.0000665062,0.9882952,0.00001142909,0.000006690426,0.001517984],"study_design_scores_gemma":[0.000008773274,0.000769179,0.5376744,0.00001334813,0.00004585937,0.0005105073,0.0004922572,0.0020418,0.4573798,0.0001021389,0.0009407513,0.00002119799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99923,0.0001132912,0.0003379252,0.00000688118,0.000001936786,0.000004735092,0.0001701729,0.000009508723,0.0001256023],"genre_scores_gemma":[0.9988011,0.00008531057,0.0005754465,0.00000574323,0.000002206794,0.000009221145,0.00028258,0.000002426224,0.0002358663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007561579,"threshold_uncertainty_score":0.001503468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03021480238203544,"score_gpt":0.2647490930754503,"score_spread":0.2345342906934149,"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."}}