{"id":"W6920456396","doi":"10.6068/dp15e70ec33099","title":"Trend 1990 - 2014. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Emissions, Land Use - Total | Country: Canada | Item: Burning Biomass | Element: Net emissions/removals (CO2) - 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Land use; Greenhouse gas; Agricultural land; Biomass (ecology); Land use, land-use change and forestry; Food security; Land management","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001265432,0.001963763,0.001742472,0.004492211,0.00105673,0.002957128,0.003145381,0.001300726,0.06216451],"category_scores_gemma":[0.008930284,0.001145104,0.001375681,0.02150523,0.0004280242,0.002845332,0.001592124,0.002654984,0.0664162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00658526,"about_ca_system_score_gemma":0.01289684,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.639796,"about_ca_topic_score_gemma":0.5649657,"domain_scores_codex":[0.9983066,0.0001483016,0.0001972683,0.0003553325,0.0006693233,0.0003231137],"domain_scores_gemma":[0.9924792,0.0005257258,0.000515302,0.0004439115,0.005687949,0.0003479281],"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":[0.00001898838,0.000008049805,0.0007288025,0.0002297625,0.00001803219,0.000005330398,0.000008003012,0.00009938434,0.00001549544,0.0002373557,0.9974023,0.001228407],"study_design_scores_gemma":[0.0001211245,0.0000104348,0.01182572,0.0004899107,0.00003526396,0.00001622678,0.0001567672,0.0002701157,0.0001692672,0.0005865345,0.9862832,0.00003542079],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003625867,0.0000283994,0.00001589613,0.00005002093,0.00002176385,0.000005724582,0.9993228,0.00003546674,0.000483823],"genre_scores_gemma":[0.0002348965,0.00008332846,0.000121123,0.00004178434,0.000008685427,0.00005044101,0.9985723,0.00003920319,0.0008481588],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9378355,"threshold_uncertainty_score":0.7246507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885005488604048,"score_gpt":0.2362991045163029,"score_spread":0.2174490496302624,"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."}}