{"id":"W4360989665","doi":"10.1016/j.ufug.2023.127918","title":"How do urban forests with different land use histories influence soil organic carbon?","year":2023,"lang":"en","type":"article","venue":"Urban forestry & urban greening","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Chinese Academy of Forestry; China Scholarship Council","keywords":"Evergreen; Soil carbon; Environmental science; Deciduous; Land use; Vegetation (pathology); Geography; Agroforestry; Forestry; Soil water; Ecology; Soil science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001516309,0.000489568,0.0004325467,0.0001175292,0.0003905384,0.0004172067,0.0005946504,0.0001796652,0.0001379368],"category_scores_gemma":[0.00004397748,0.0003554795,0.00009796582,0.0007353098,0.0001097917,0.0009467291,0.0004053219,0.0003118354,0.0001201319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002811546,"about_ca_system_score_gemma":0.00002857927,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001931853,"about_ca_topic_score_gemma":0.01816429,"domain_scores_codex":[0.9972247,0.0000634891,0.0003334043,0.0007632261,0.0007149979,0.0009002174],"domain_scores_gemma":[0.9985332,0.0001193285,0.0002362294,0.0007505924,0.00002696906,0.0003336118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006008749,0.00002872544,0.9924948,0.00006623741,0.00005024467,0.0001238211,0.00137559,0.00098718,0.0002882524,0.00002651613,0.004420952,0.00007765058],"study_design_scores_gemma":[0.0008112643,0.0002505884,0.984198,0.0002123626,0.00009135612,0.00003238861,0.0001939677,0.005531053,0.0004757015,0.0001123128,0.00738379,0.0007072387],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981934,0.0001897855,0.00002562036,0.0001821936,0.0002726012,0.0003019675,0.00002177341,0.000409026,0.0004036435],"genre_scores_gemma":[0.9962118,0.00001393557,0.00004287943,0.00006343852,0.0003050028,0.00005497232,0.00005627939,0.00008861847,0.003163022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01623243,"threshold_uncertainty_score":0.9998897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005444214974374,"score_gpt":0.1809914370191451,"score_spread":0.1709369948694013,"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."}}