{"id":"W4309995064","doi":"10.1101/2022.11.24.517857","title":"Dynamics of methane cycling microbiome during methane flux hot moments from riparian buffer systems","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Environment and Climate Change Canada; University of Guelph","funders":"Agriculture and Agri-Food Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Riparian zone; Environmental science; Soil water; Riparian buffer; Ecology; Hydrology (agriculture); Biology; Habitat; Soil science; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001156838,0.00028902,0.0004758725,0.0006343307,0.0005925278,0.0006454964,0.0002074631,0.0002811548,0.0007740223],"category_scores_gemma":[0.0002311855,0.000199867,0.0002163319,0.0006841146,0.0002871036,0.0003614007,0.000513515,0.0003322214,0.0002047129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004396692,"about_ca_system_score_gemma":0.0004473094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01655479,"about_ca_topic_score_gemma":0.03791444,"domain_scores_codex":[0.9998336,0.000008278083,0.000005867778,0.00006002053,0.00002946479,0.00006282388],"domain_scores_gemma":[0.9998221,0.00001186496,0.00004097282,0.000005905673,0.00006118367,0.00005804887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00101302,0.0001320358,0.5695119,0.0001870382,0.000084705,0.0005852029,0.002507232,0.0003039603,0.4120783,0.0001009033,0.0004734824,0.01302228],"study_design_scores_gemma":[0.000003616813,0.00009989183,0.9924747,0.000009654615,0.00002025852,0.00009556903,0.001461297,0.0002785997,0.004752463,0.00002674066,0.0007654996,0.00001164607],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987665,0.0001396052,0.0001044716,0.00001010722,0.000002160391,0.000007072712,0.0007613682,0.000005672644,0.0002031587],"genre_scores_gemma":[0.9966424,0.0001848942,0.0003762071,0.00004511964,0.000004720052,0.00002339078,0.002056886,0.000008287877,0.0006581256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01655479,"threshold_uncertainty_score":0.0329169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198562906809366,"score_gpt":0.2161939813209324,"score_spread":0.2042083522528387,"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."}}