{"id":"W7055260951","doi":"","title":"Clean Fuel and Electric Vehicle Use in Canada Can Reduce GHGs by over 50 Million Tonnes by 2030 – Advanced BioFuels USA","year":2019,"lang":"en","type":"other","venue":"","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Tonne; Biofuel; Greenhouse gas; Electricity; Renewable energy; Electric vehicle; Fuel efficiency; Green vehicle","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":[],"consensus_categories":[],"category_scores_codex":[0.0004238086,0.0006389618,0.000162114,0.001010762,0.002487408,0.001865543,0.0005875298,0.001006132,0.05293],"category_scores_gemma":[0.0007203048,0.0002110337,0.0006037977,0.001031898,0.0005233373,0.0007160181,0.001121149,0.001272752,0.009602525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01806349,"about_ca_system_score_gemma":0.07247069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9703561,"about_ca_topic_score_gemma":0.9873847,"domain_scores_codex":[0.9995089,0.000009999505,0.000004949028,0.00002086205,0.0002781079,0.0001772081],"domain_scores_gemma":[0.9991309,0.00001458469,0.00001616128,0.00001784842,0.000643649,0.0001768309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001846431,0.0001228347,0.003705429,0.0002232512,0.00003097827,0.0001359036,0.00009057897,0.0008643592,0.002686095,0.01974354,0.8567532,0.1154592],"study_design_scores_gemma":[0.00002308278,0.00001963095,0.008668845,0.00008409243,0.00001509716,0.00002988231,0.0001995009,0.0005187931,0.001481238,0.001745886,0.9871962,0.00001770524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01601344,0.003169201,0.001734269,0.01671145,0.00141467,0.0002208403,0.03107814,0.0009299081,0.9287282],"genre_scores_gemma":[0.0655022,0.005005595,0.004076211,0.004202551,0.0001424153,0.00006930926,0.01258923,0.0002756405,0.9081368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05293,"threshold_uncertainty_score":0.1770685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006486312461456545,"score_gpt":0.2255254584841334,"score_spread":0.2190391460226769,"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."}}