{"id":"W2019459816","doi":"10.1016/j.agee.2009.12.008","title":"A tool to link agricultural activity data with the DNDC model to estimate GHG emission factors in Canada","year":2010,"lang":"en","type":"article","venue":"Agriculture Ecosystems & Environment","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":113,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Greenhouse gas; Environmental science; Agriculture; Climate change; Tier 1 network; Environmental resource management; Range (aeronautics); Atmospheric sciences; Computer science; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005678383,0.0005533261,0.0003435244,0.001671836,0.001006883,0.001051278,0.0008438629,0.0003876869,0.004662369],"category_scores_gemma":[0.002869533,0.0004290904,0.0004017875,0.002980156,0.0001718199,0.000546737,0.0003673997,0.0003858311,0.0008251526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009274399,"about_ca_system_score_gemma":0.01167525,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9789138,"about_ca_topic_score_gemma":0.9702849,"domain_scores_codex":[0.9997882,0.00002165383,0.00001600883,0.00004773196,0.00009324987,0.0000332532],"domain_scores_gemma":[0.9987981,0.000172696,0.00005457346,0.0000645175,0.0008500991,0.00006002422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002728861,0.0001810528,0.1080307,0.0002373049,0.0003191668,0.0002581217,0.0002691643,0.6386489,0.003788227,0.005852467,0.05079333,0.1913486],"study_design_scores_gemma":[0.00009612228,0.00001568098,0.03200931,0.00004758955,0.00008605628,0.00003568572,0.0001755034,0.9303112,0.004690811,0.001867736,0.03060557,0.00005861721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5827177,0.0006757016,0.1839045,0.001494001,0.0002325597,0.0005085993,0.1516701,0.03452937,0.04426747],"genre_scores_gemma":[0.8074968,0.0003930243,0.1458163,0.0001546804,0.00001988866,0.0002141755,0.03646487,0.0008336465,0.008606487],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02108622,"threshold_uncertainty_score":0.06729072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132651332394645,"score_gpt":0.1960245216486032,"score_spread":0.1846980083246567,"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."}}