{"id":"W3087067048","doi":"10.1111/ejss.13049","title":"Long‐term legacy of land‐use change in soils from a subtropical rainforest: Relating microbiological and physicochemical parameters","year":2020,"lang":"en","type":"article","venue":"European Journal of Soil Science","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires; Agencia Nacional de Promoción Científica y Tecnológica; Fondo para la Investigación Científica y Tecnológica; Universidad de Buenos Aires","keywords":"Environmental science; Land use, land-use change and forestry; Biomass (ecology); Land use; Abiotic component; Ecosystem; Soil carbon; Soil water; Nutrient; Subtropics; Microbial population biology; Agricultural land; Soil organic matter; Agronomy; Agroforestry; Ecology; Soil science; Biology","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":[0.0004113812,0.0002871677,0.0002990353,0.000831369,0.0004336877,0.0006300372,0.000261417,0.0003645647,0.0004562781],"category_scores_gemma":[0.0003929137,0.0001264964,0.0003038655,0.001219478,0.0004635314,0.000429172,0.0004109763,0.0002510743,0.0001144898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003840974,"about_ca_system_score_gemma":0.0002663572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01081647,"about_ca_topic_score_gemma":0.01726018,"domain_scores_codex":[0.9998009,0.0000308072,0.00002079244,0.00005914896,0.00004773575,0.00004069434],"domain_scores_gemma":[0.9994931,0.00005725806,0.0001728439,0.00004296683,0.0001594148,0.00007430775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001005164,0.00004802899,0.9677312,0.00004598605,0.0001273511,0.0001980605,0.0002755238,0.0001531292,0.02738131,0.0000204034,0.00004903109,0.003869466],"study_design_scores_gemma":[5.528821e-7,0.00001874549,0.9992337,0.000001619352,0.0000118035,0.0000308561,0.0001551181,0.0001065907,0.0003536488,0.000008173863,0.00007738448,0.000001711773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994072,0.0001582418,0.00007968408,0.0000124466,0.000002258972,0.000003398708,0.0001962324,0.000001913541,0.0001387301],"genre_scores_gemma":[0.9994248,0.00007815623,0.0001095399,0.0000148291,0.0000054716,0.000005263447,0.0003057373,0.000001205296,0.00005497819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01081647,"threshold_uncertainty_score":0.02150697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04742849710848576,"score_gpt":0.2301385804865447,"score_spread":0.1827100833780589,"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."}}