{"id":"W6938948477","doi":"10.6068/dp14baa2fa49354","title":"Trend 2002 - 2009. Statistics Canada. CANSIM: Environment - Natural Resources | Country: Canada | Province: New Brunswick | Table: Supply and demand of primary and secondary energy in natural units | Variable: Aviation gasoline, secondary energy, Availability | Units: Megalitres, 2002-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-086.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Natural resource; Census; Official statistics; Summary statistics; Descriptive statistics; Natural (archaeology); International comparisons","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":[0.002031107,0.002448228,0.002569851,0.008747092,0.003384525,0.005454691,0.004892839,0.001492892,0.1062162],"category_scores_gemma":[0.01646485,0.00196653,0.002164884,0.04323558,0.0006655611,0.002889293,0.002283009,0.003193204,0.06180474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06121126,"about_ca_system_score_gemma":0.1622946,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9956578,"about_ca_topic_score_gemma":0.9937714,"domain_scores_codex":[0.9956965,0.0002611992,0.0004765881,0.0005294396,0.002007149,0.001029121],"domain_scores_gemma":[0.9657667,0.001111856,0.0009161994,0.000983956,0.02967328,0.001547984],"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":[0.0000209291,0.000006184364,0.00100471,0.0002329491,0.00002081367,0.000007846795,0.00002143196,0.0001329469,0.00001082611,0.000488009,0.9963086,0.001744719],"study_design_scores_gemma":[0.0001170603,0.000008989045,0.01781061,0.0007231703,0.00005323013,0.00002568905,0.0004506055,0.0004905761,0.0001848954,0.0006855064,0.9793658,0.00008382081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005377069,0.00005494345,0.00003069198,0.0001484193,0.00003817151,0.00001666409,0.9981839,0.00007099945,0.001402425],"genre_scores_gemma":[0.001142852,0.0003866481,0.0005800505,0.0002068505,0.0000210873,0.0001473861,0.9904969,0.00017752,0.006840831],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1062162,"threshold_uncertainty_score":0.4441208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105257286989453,"score_gpt":0.2009761345075929,"score_spread":0.1904504058086476,"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."}}