{"id":"W3107170851","doi":"10.18174/533503","title":"Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020","year":2020,"lang":"nl","type":"report","venue":"","topic":"Climate Change and Environmental Impact","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Greenhouse gas; Context (archaeology); Carbon dioxide; Methane; Environmental science; Forestry; Particulates; Land use, land-use change and forestry; Agriculture; Chemistry; Geography","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":[0.001789128,0.0004902866,0.0004187612,0.001347633,0.000718181,0.002906514,0.0007373657,0.000972948,0.0278564],"category_scores_gemma":[0.002772501,0.0003201957,0.0005218753,0.00287329,0.0002390914,0.001827525,0.001106632,0.001275349,0.007463049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003484338,"about_ca_system_score_gemma":0.007929024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1737551,"about_ca_topic_score_gemma":0.2256947,"domain_scores_codex":[0.9982151,0.0002584327,0.0001518915,0.0001514969,0.001005748,0.0002174166],"domain_scores_gemma":[0.9991902,0.0001416856,0.0001188641,0.00004536368,0.000403942,0.00009996589],"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":[0.0003109378,0.0001657559,0.01332568,0.002509031,0.0001424395,0.0006727459,0.002313993,0.005376568,0.007176713,0.03617212,0.7016147,0.2302194],"study_design_scores_gemma":[0.000009752089,0.00001952797,0.01212502,0.0002295433,0.00002707929,0.00007924186,0.0007331141,0.0003539164,0.001991186,0.001108949,0.9832988,0.00002383735],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06731839,0.04755089,0.02335007,0.02050471,0.005932817,0.0006318848,0.2379183,0.001669601,0.5951232],"genre_scores_gemma":[0.1821592,0.05394828,0.03230914,0.003171471,0.0007050849,0.00139595,0.2045698,0.001392785,0.5203483],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1737551,"threshold_uncertainty_score":0.3454875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732385599329357,"score_gpt":0.284339894593354,"score_spread":0.2570160386000604,"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."}}