{"id":"W2355153335","doi":"","title":"N INTERNAL CYCLING IN LEYMUS CHINENSIS GRASSLAND VEGETATION-SOIL SYSTEM","year":2003,"lang":"en","type":"article","venue":"Acta Phytoecologica Sinica","topic":"Plant Growth and Agriculture Techniques","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soil test; Litter; Quadrat; Kjeldahl method; Plant litter; Environmental science; Vegetation (pathology); Biomass (ecology); Grassland; Cycling; Animal science; Leymus; Agronomy; Ecosystem; Soil water; Chemistry; Forestry; Transect; Soil science; Nitrogen; Ecology; Biology; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009142161,0.0001733933,0.0001863862,0.0005868999,0.0003472705,0.0003309355,0.0001874328,0.0001687112,0.0004819815],"category_scores_gemma":[0.0001329431,0.000112008,0.0001703069,0.000392138,0.0001882821,0.0002245347,0.0003261172,0.00007698539,0.00006857912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005441902,"about_ca_system_score_gemma":0.0003554315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02449542,"about_ca_topic_score_gemma":0.06157411,"domain_scores_codex":[0.999939,0.000009033603,0.000004944495,0.00002223611,0.00001111001,0.00001379784],"domain_scores_gemma":[0.9999002,0.00001043999,0.00003480426,0.000007335128,0.00001858232,0.00002858188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003196621,0.0000515316,0.8305537,0.000130844,0.0001202397,0.0003177676,0.0008191823,0.0005618287,0.1570142,0.000119396,0.00006564132,0.009925997],"study_design_scores_gemma":[0.00000341669,0.00006169238,0.997236,0.000003111315,0.00001673843,0.000112977,0.0002135922,0.0008697556,0.00124637,0.00003300836,0.000197332,0.000006065346],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997112,0.00004672628,0.00003812357,0.000002662742,2.396793e-7,0.000001237948,0.00005126801,0.000003304747,0.0001451633],"genre_scores_gemma":[0.9996027,0.00003399825,0.0000685156,0.000005913743,6.165877e-7,0.000003872011,0.0001617147,0.000001510106,0.0001211851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02449542,"threshold_uncertainty_score":0.0487057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009635739469672479,"score_gpt":0.2002496088409879,"score_spread":0.1906138693713154,"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."}}