{"id":"W3198660624","doi":"","title":"Agriculture in the Boreal Forest: Understanding the Impact of Land Use Change on Soil Carbon for Developing Sustainable Community Food Systems","year":2020,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Environmental science; Agriculture; Land use; Sustainable agriculture; Agroforestry; Soil carbon; Land use, land-use change and forestry; Taiga; Agricultural land; Natural resource economics; Geography; Forestry; Soil water; Soil science; Ecology; Economics","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":[0.000602165,0.0002634442,0.0001977768,0.0002999871,0.0003920386,0.001304772,0.0004291684,0.0005541595,0.001180253],"category_scores_gemma":[0.0005392588,0.00009363163,0.0002064923,0.0004870944,0.0009842404,0.001887683,0.0003553402,0.0004387759,0.00006267588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379555,"about_ca_system_score_gemma":0.001499332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.107083,"about_ca_topic_score_gemma":0.2231728,"domain_scores_codex":[0.9998788,0.00003264836,0.000003903558,0.0000259175,0.00001674685,0.0000420042],"domain_scores_gemma":[0.999804,0.00006078963,0.00005919558,0.000007153044,0.00002717413,0.00004169397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006742727,0.0006172516,0.7073827,0.001520451,0.0003822232,0.001133265,0.004039179,0.02142877,0.02707002,0.02030087,0.006549099,0.2089019],"study_design_scores_gemma":[0.00002009415,0.000137915,0.956219,0.0001089509,0.00008683138,0.0001945744,0.006914593,0.01227538,0.0007955199,0.01312692,0.01009076,0.00002936626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671048,0.01393826,0.001146463,0.008025099,0.00007104794,0.0000145032,0.0002873375,0.00001813616,0.009394342],"genre_scores_gemma":[0.9940924,0.004663406,0.0005104858,0.0002640907,0.00003985634,0.000004887123,0.00006548204,0.000003164051,0.000356384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.107083,"threshold_uncertainty_score":0.2129194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1232339665769562,"score_gpt":0.2791926033125114,"score_spread":0.1559586367355552,"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."}}