{"id":"W2784545593","doi":"10.1016/j.rser.2018.11.025","title":"The role of bioenergy in low-carbon energy transition scenarios: A case study for Quebec (Canada)","year":2018,"lang":"en","type":"article","venue":"Renewable and Sustainable Energy Reviews","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Group for Research in Decision Analysis; HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; BioFuelNet Canada","keywords":"Bioenergy; Greenhouse gas; Scenario analysis; Natural resource economics; Baseline (sea); Environmental science; Government (linguistics); Energy policy; Agricultural economics; Environmental protection; Environmental economics; Business; Renewable energy; Economics; Biofuel; Engineering; Waste management; Political science; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007611739,0.0004675894,0.000255322,0.0008538398,0.00550024,0.00401606,0.001366422,0.001815251,0.003949036],"category_scores_gemma":[0.001057428,0.0001733521,0.0005339648,0.00190484,0.001483879,0.0009133979,0.0009184574,0.001012403,0.0001761331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08224232,"about_ca_system_score_gemma":0.0435797,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951108,"about_ca_topic_score_gemma":0.9980658,"domain_scores_codex":[0.99938,0.0001243812,0.000009821978,0.00003708679,0.0001208614,0.0003279989],"domain_scores_gemma":[0.9993126,0.0001548363,0.00003349091,0.00001734558,0.0002953555,0.0001864387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00196547,0.001148846,0.2043922,0.001265778,0.0005511533,0.02965175,0.01614189,0.2713176,0.01630719,0.1707878,0.09770061,0.1887697],"study_design_scores_gemma":[0.0003942498,0.000670503,0.2765944,0.001071785,0.0005421917,0.001772131,0.1458676,0.168578,0.00843034,0.01550013,0.380123,0.000455552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8936686,0.002839227,0.002002679,0.006385524,0.00006763723,0.0002720752,0.002145577,0.00007102571,0.09254769],"genre_scores_gemma":[0.9810495,0.0009357051,0.001471926,0.0003755232,0.000004868968,0.00003140087,0.0003238536,0.00001989514,0.01578734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08224232,"threshold_uncertainty_score":0.5967126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005657670679013549,"score_gpt":0.2180869471853236,"score_spread":0.21242927650631,"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."}}