{"id":"W3091866296","doi":"10.1101/2020.10.08.332528","title":"Common physiological processes control mercury reduction during photosynthesis and fermentation","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Geological Survey","keywords":"Anoxygenic photosynthesis; Anoxic waters; Environmental chemistry; Isotope fractionation; Photosynthesis; Chemistry; Mercury (programming language); Fermentation; Fractionation; Biochemistry; Phototroph; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001381226,0.0003027277,0.0003107278,0.0001660211,0.0002408288,0.0005363863,0.0002641981,0.0004133205,0.000611732],"category_scores_gemma":[0.0002089636,0.0001573249,0.0002571758,0.0001946358,0.0002513478,0.0002994293,0.0005931361,0.0004461637,0.0002304773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004717325,"about_ca_system_score_gemma":0.0002807841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002712023,"about_ca_topic_score_gemma":0.001815247,"domain_scores_codex":[0.9998035,0.00001423279,0.00001070294,0.00007207565,0.00005785507,0.00004165289],"domain_scores_gemma":[0.9998647,0.00002403105,0.00003518407,0.0000178977,0.00003144218,0.00002670495],"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":[0.00004764214,0.00001012863,0.001543436,0.00002822176,0.000003853631,0.0000356717,0.00003400022,0.00007591755,0.9972144,0.00007718112,0.00002491897,0.0009046713],"study_design_scores_gemma":[0.00000735559,0.0002561363,0.1158856,0.00001682302,0.00001599887,0.0002157276,0.0003107982,0.002984578,0.8771999,0.0003553815,0.002725249,0.00002644367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927607,0.0007100042,0.00371699,0.0001420745,0.00002673161,0.00002379636,0.0007421568,0.0001278917,0.001749681],"genre_scores_gemma":[0.9970499,0.0001945434,0.001339363,0.00004324203,0.000004504523,0.0000162104,0.0004635896,0.00001910587,0.0008693868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002712023,"threshold_uncertainty_score":0.005392432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992365804949685,"score_gpt":0.2344377604236622,"score_spread":0.2145141023741653,"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."}}