{"id":"W1817009495","doi":"10.15353/cfs-rcea.v2i2.102","title":"SFSGEC - Learning from the failures of biofuels governance","year":2015,"lang":"en","type":"article","venue":"Canadian Food Studies / La Revue canadienne des études sur l alimentation","topic":"Oil Palm Production and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Biofuel; Greenhouse gas; Monoculture; Land use, land-use change and forestry; Agriculture; Natural resource economics; Fossil fuel; Climate change; Environmental science; Biodiversity; Sustainability; Land use; Business; Fertilizer; Agricultural economics; Agroforestry; Economics; Agronomy; Engineering; Waste management; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005906466,0.0001728554,0.0002194524,0.00003329006,0.0003078422,0.00003246305,0.0002508744,0.0000546913,0.0001299261],"category_scores_gemma":[0.0008473258,0.000149843,0.00006026231,0.0003747336,0.0005792456,0.0002576666,0.00007688449,0.0001433664,0.00002140729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002276381,"about_ca_system_score_gemma":0.0001416198,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5704036,"about_ca_topic_score_gemma":0.9741929,"domain_scores_codex":[0.9985641,0.0002146095,0.0002840114,0.0003651202,0.0001457596,0.0004264402],"domain_scores_gemma":[0.9988655,0.0001773912,0.0001596899,0.000283892,0.0001317975,0.0003817714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009367804,0.00009252188,0.7733305,0.0001597066,0.0007703638,0.00006135492,0.1342746,0.01172101,0.001478032,0.009603169,0.007147373,0.06126777],"study_design_scores_gemma":[0.001134623,0.0006440227,0.5922985,0.0001072928,0.0001649316,0.00002253011,0.1337308,0.0002041965,0.001551493,0.009165966,0.2603014,0.0006741805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923412,0.001188118,0.000007117493,0.003454861,0.0002381284,0.0002495414,0.0000552415,0.00002107521,0.00244467],"genre_scores_gemma":[0.9987566,0.00009780181,0.0001740826,0.0002469864,0.00006288091,0.0000376799,0.00002297023,0.00001669675,0.0005843015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4037892,"threshold_uncertainty_score":0.6110421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0459116535640379,"score_gpt":0.2347298079186554,"score_spread":0.1888181543546175,"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."}}