{"id":"W65142205","doi":"10.1023/a:1012605212388","title":"Soil-land-use-system approach to estimate nitrous oxide emissions from agricultural soils","year":2001,"lang":"en","type":"article","venue":"Nutrient Cycling in Agroecosystems","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Environmental science; Soil water; Land use; Greenhouse gas; Agriculture; Macro; Spatial analysis; Land management; Geographic information system; Environmental resource management; Sustainability; Agricultural land; Geography; Soil science; Ecology; Remote sensing; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006128381,0.0005216253,0.00038827,0.000891862,0.0005068197,0.0004114551,0.0005743163,0.0004704473,0.00062837],"category_scores_gemma":[0.0007490295,0.0002549736,0.0006268851,0.001204266,0.0002193747,0.0005034112,0.0004465626,0.0002172793,0.0001221466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519254,"about_ca_system_score_gemma":0.0008528108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05577736,"about_ca_topic_score_gemma":0.0704838,"domain_scores_codex":[0.9997521,0.0001191571,0.00001690522,0.0000613408,0.00003181339,0.00001864557],"domain_scores_gemma":[0.9996843,0.0001673832,0.00004764551,0.00002816836,0.00005162301,0.00002083134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005511905,0.0005259074,0.4784528,0.0002394562,0.001805755,0.0002369615,0.000184321,0.4413902,0.02778398,0.002983418,0.0006031526,0.0452428],"study_design_scores_gemma":[0.00004808371,0.0001595405,0.1651022,0.000006531771,0.0002064938,0.00007717714,0.0001189339,0.8270761,0.004853079,0.00131622,0.001011313,0.00002423794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980073,0.0001993346,0.017699,0.00004686136,0.00001235094,0.00005974655,0.000924001,0.00007581322,0.0009097751],"genre_scores_gemma":[0.9905719,0.00007218098,0.008634212,0.00001282456,0.000004777042,0.00005515134,0.0003153129,0.000008881438,0.0003247393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05577736,"threshold_uncertainty_score":0.1109054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02255029125009949,"score_gpt":0.2365681666974907,"score_spread":0.2140178754473912,"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."}}