{"id":"W6938814248","doi":"10.6068/dp15dfe11d37510","title":"Trend 1990 - 2014. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Emissions, Land Use - Total | Country: Canada | Item: Grassland | Element: Net emissions/removals (CO2eq) - Gigagrams, 1990-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 067-001-041.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Asian Studies and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Land use; Greenhouse gas; Agricultural land; Land use, land-use change and forestry; Food security; Land management; Geospatial analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001256276,0.00198045,0.001798184,0.004583714,0.001068773,0.003000609,0.00318173,0.001273175,0.06307577],"category_scores_gemma":[0.008778644,0.001149629,0.001418531,0.02242546,0.000435949,0.002757464,0.001591955,0.002630483,0.06340123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007348616,"about_ca_system_score_gemma":0.01477385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.70758,"about_ca_topic_score_gemma":0.6301068,"domain_scores_codex":[0.9982894,0.0001418432,0.0001941462,0.000354273,0.000692076,0.0003281969],"domain_scores_gemma":[0.9923221,0.0005067475,0.0005034945,0.0004256627,0.005887258,0.0003547202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002039428,0.000008051649,0.0007482291,0.0002491508,0.00002007923,0.000005546138,0.000008454554,0.0001030567,0.00001667482,0.0002411916,0.9972818,0.001297286],"study_design_scores_gemma":[0.0001230616,0.00001047986,0.01238366,0.0004935733,0.00003794424,0.00001601331,0.0001535502,0.0002736896,0.0001765422,0.0005707309,0.9857234,0.00003723785],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003587994,0.00002966987,0.00001621314,0.00005073334,0.00002117991,0.000005856797,0.9993119,0.00003733941,0.0004911261],"genre_scores_gemma":[0.0002513743,0.00009204508,0.0001316108,0.00004551871,0.000008600922,0.00005128359,0.9984848,0.00004286307,0.0008918057],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.29242,"threshold_uncertainty_score":0.5882841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847989915149408,"score_gpt":0.2418358160606466,"score_spread":0.2233559169091525,"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."}}