{"id":"W1599034928","doi":"10.1038/35070643","title":"Animal nitrogen swap for plant carbon","year":2001,"lang":"en","type":"article","venue":"Nature","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":164,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Nutrient; Ecology; Boreal; Swap (finance); Temperate climate; Environmental 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":[0.0006842649,0.0004337892,0.0004757858,0.0004399656,0.0004876879,0.0007155631,0.0004939255,0.001067719,0.01182217],"category_scores_gemma":[0.0007047094,0.0001739464,0.0003996333,0.0003534837,0.001159014,0.001350472,0.0007373955,0.0008360325,0.0009361329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008834999,"about_ca_system_score_gemma":0.0005723466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000597685,"about_ca_topic_score_gemma":0.0007759805,"domain_scores_codex":[0.9997644,0.0000419045,0.00000833893,0.0000670069,0.00007787871,0.00004050816],"domain_scores_gemma":[0.9996033,0.0001125687,0.00004426913,0.0001067628,0.00004853735,0.00008449594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002565481,0.0002304886,0.007305935,0.0005630825,0.0003479187,0.0006815104,0.0001393727,0.005913078,0.7891932,0.107371,0.001836615,0.08385241],"study_design_scores_gemma":[0.0004049794,0.00224509,0.06279248,0.000165823,0.000368363,0.002948472,0.0005683433,0.01779617,0.6804622,0.1445901,0.08754294,0.000114951],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299306,0.007268294,0.017457,0.003921538,0.0007030587,0.00003874919,0.0005172926,0.0003478953,0.03981565],"genre_scores_gemma":[0.9867743,0.0009009083,0.002872456,0.0003960603,0.00005636073,0.00001378092,0.0001256218,0.00007082371,0.008789644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01182217,"threshold_uncertainty_score":0.03954905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771132770317994,"score_gpt":0.2179218691939983,"score_spread":0.1902105414908183,"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."}}