{"id":"W2043703737","doi":"10.1016/j.agee.2014.10.009","title":"Carbon stock and change from woody biomass on Canada’s cropland between 1990 and 2000","year":2015,"lang":"en","type":"article","venue":"Agriculture Ecosystems & Environment","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Environmental science; Carbon sequestration; Perennial plant; Herbaceous plant; Climate change; Greenhouse gas; Carbon sink; Vegetation (pathology); Forestry; Woody plant; Agricultural land; Agroforestry; Carbon stock; Biomass (ecology); Agriculture; Agronomy; Geography; Ecology; Carbon dioxide; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004061543,0.000312078,0.0002281444,0.001686011,0.001028161,0.001123677,0.0008309002,0.0007694146,0.003121857],"category_scores_gemma":[0.001648614,0.0002804718,0.0005685591,0.00324504,0.0005486918,0.0006278355,0.0006329145,0.0008288453,0.0003825641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01618264,"about_ca_system_score_gemma":0.01304388,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9918268,"about_ca_topic_score_gemma":0.9965979,"domain_scores_codex":[0.9997159,0.00001320165,0.00001902621,0.00005046657,0.00008976362,0.0001116667],"domain_scores_gemma":[0.998161,0.0001448988,0.0004154195,0.00005029969,0.000780794,0.0004475983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002353006,0.00004211171,0.9847905,0.00006924459,0.0001644847,0.0001557396,0.000486018,0.001038589,0.0004655601,0.0005657856,0.004666623,0.007320023],"study_design_scores_gemma":[0.000005454115,0.000006594843,0.9963861,0.00002550481,0.00002559882,0.00004283269,0.0003397906,0.0004691124,0.0001226137,0.00004335507,0.002525693,0.000007303991],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703268,0.001902487,0.000115048,0.0008288826,0.00003914742,0.000009396761,0.02367544,0.00002748289,0.003075408],"genre_scores_gemma":[0.985522,0.0007821936,0.0001219083,0.0001403148,0.00001276178,0.00000597896,0.009333902,0.000007152276,0.004073752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01618264,"threshold_uncertainty_score":0.1174139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160601534730725,"score_gpt":0.1728438241463383,"score_spread":0.161237808799031,"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."}}