{"id":"W3135655082","doi":"10.5194/egusphere-egu21-1105","title":"Long-term silicon dynamics in terrestrial ecosystems: insights from 2-million years soil chronosequences","year":2021,"lang":"en","type":"article","venue":"","topic":"Silicon Effects in Agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Université de Montréal","funders":"","keywords":"Weathering; Chronosequence; Soil water; Soil production function; Geology; Bioturbation; Soil carbon; Carbonate; Silicate; Ecosystem; Soil science; Environmental chemistry; Environmental science; Geochemistry; Pedogenesis; Chemistry; Ecology; Sediment; Geomorphology","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":[0.0002391867,0.0001860538,0.0002330234,0.001111356,0.000356571,0.0004107035,0.0002041029,0.0002851991,0.0005145594],"category_scores_gemma":[0.0003017909,0.0001868559,0.0002739007,0.001190122,0.0002072047,0.0003401289,0.0003814868,0.0001862977,0.0001377179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003267422,"about_ca_system_score_gemma":0.0001915357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02395693,"about_ca_topic_score_gemma":0.05742036,"domain_scores_codex":[0.9999421,0.000006113848,0.000004699458,0.00002714465,0.000009845786,0.00001018354],"domain_scores_gemma":[0.9997484,0.00002925788,0.00008922252,0.00002375362,0.00006781015,0.00004147405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008790849,0.00002945602,0.9401787,0.00008897213,0.0001752061,0.0002555136,0.001199925,0.0005982188,0.04437982,0.0001004531,0.000240794,0.01266517],"study_design_scores_gemma":[5.628006e-7,0.000005942237,0.9990788,0.00000227061,0.000009103686,0.00002878831,0.00005916461,0.0001959047,0.000201374,0.000008614628,0.0004076979,0.000001741068],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985213,0.0003654097,0.0002033084,0.00001437357,0.000002196075,0.000003563949,0.0005736693,0.000007045867,0.0003092193],"genre_scores_gemma":[0.9976268,0.0003268264,0.0006749529,0.00002018033,0.000005790625,0.00001322757,0.00109897,0.000006861758,0.0002262839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02395693,"threshold_uncertainty_score":0.04763496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225154042491959,"score_gpt":0.218117119483125,"score_spread":0.2058655790582054,"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."}}