{"id":"W3003607031","doi":"10.18174/501680","title":"Meerkosten biodiversiteitsmaatregelen voor melkvee- en akkerbouwbedrijven","year":2019,"lang":"nl","type":"report","venue":"","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Arable land; Hectare; Agricultural science; Agriculture; Geography; Agroforestry; Business; Environmental science","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":[0.002801954,0.000781448,0.0007433766,0.001811384,0.0006877407,0.003416501,0.0008046531,0.0007066568,0.03513517],"category_scores_gemma":[0.003273326,0.0005049933,0.0007668008,0.001918192,0.0007685566,0.001991391,0.002090831,0.001200805,0.0066178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001644637,"about_ca_system_score_gemma":0.001638948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009525049,"about_ca_topic_score_gemma":0.02294585,"domain_scores_codex":[0.9974977,0.0003903074,0.0001465849,0.0004824162,0.001214272,0.0002686294],"domain_scores_gemma":[0.9974981,0.0006163446,0.0005003936,0.0001994559,0.0007868615,0.0003988447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001891114,0.0006814688,0.2101614,0.00233635,0.0006195714,0.000399792,0.004878087,0.007558737,0.09207808,0.01789564,0.01921684,0.6422829],"study_design_scores_gemma":[0.00005623532,0.0009812595,0.5479649,0.0006582872,0.0003560386,0.0004342929,0.005515883,0.002472463,0.05226684,0.01272494,0.3763289,0.0002398462],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.664827,0.006132287,0.03597454,0.00221219,0.0004399407,0.0003246292,0.01075603,0.001004405,0.278329],"genre_scores_gemma":[0.8006421,0.004293192,0.02487614,0.0004339546,0.0001155458,0.0003367426,0.009648317,0.0007249381,0.1589289],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03513517,"threshold_uncertainty_score":0.1175389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01775249483259987,"score_gpt":0.2254751726170122,"score_spread":0.2077226777844123,"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."}}