{"id":"W4385437898","doi":"10.1016/j.agee.2023.108683","title":"Phosphorus loss management and crop yields: A global meta-analysis","year":2023,"lang":"en","type":"article","venue":"Agriculture Ecosystems & Environment","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Environmental science; Intercropping; Straw; Crop yield; Crop; Irrigation; Agronomy; Nutrient management; Agricultural engineering; Agriculture; Mathematics; Biology; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01196418,0.003153491,0.00614601,0.002572156,0.0007198365,0.002491327,0.003155411,0.002044666,0.005257764],"category_scores_gemma":[0.01112178,0.001510535,0.03328656,0.00391861,0.0008438585,0.001147705,0.002480425,0.002465256,0.0004928025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011993,"about_ca_system_score_gemma":0.001942342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02682845,"about_ca_topic_score_gemma":0.02478734,"domain_scores_codex":[0.9932166,0.004308545,0.0003946342,0.001497892,0.0002067243,0.0003756601],"domain_scores_gemma":[0.9872858,0.009343142,0.0008643342,0.001629911,0.0004148183,0.0004619691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.003422227,0.00008421304,0.04722276,0.004226895,0.9209739,0.000402944,0.0001018776,0.01492576,0.00134075,0.0003097038,0.001320346,0.005668638],"study_design_scores_gemma":[0.001377394,0.0006253821,0.05990249,0.0006284059,0.9177312,0.0002602928,0.0002059049,0.01470653,0.0005700204,0.001051092,0.00282149,0.0001197062],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7676727,0.1881315,0.0225155,0.003392893,0.0009791522,0.0001986832,0.01470376,0.0008824298,0.001523346],"genre_scores_gemma":[0.9855839,0.005870394,0.004650957,0.0005895371,0.0001138894,0.0001207147,0.00223459,0.0001838186,0.0006523067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02682845,"threshold_uncertainty_score":0.06327343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01176925156401964,"score_gpt":0.195187025430942,"score_spread":0.1834177738669223,"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."}}