{"id":"W6976870632","doi":"10.6068/dp14baa3070d634","title":"Trend 1999 - 2012. Statistics Canada. CANSIM: Energy - Petroleum Products | Country: Canada | Province: New Brunswick | Table: Supply and demand of refined petroleum products for non-energy use | Variable: Asphalt, Commercial and other institutional | Units: Megalitres, 1999-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-080.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Petroleum; Petroleum product; Economic statistics; Product (mathematics); Summary statistics; Official statistics; Oil refinery; Descriptive statistics; Energy source; Energy supply","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":[0.001705671,0.002454335,0.002495383,0.008564256,0.00305423,0.004748667,0.004554354,0.001430607,0.09476074],"category_scores_gemma":[0.01483799,0.001708987,0.002125931,0.04222111,0.0005971976,0.002698807,0.002058226,0.002882628,0.0562235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05111311,"about_ca_system_score_gemma":0.1299286,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946584,"about_ca_topic_score_gemma":0.9927128,"domain_scores_codex":[0.9964401,0.0001969832,0.0003785899,0.0004498,0.001665619,0.0008689545],"domain_scores_gemma":[0.9722334,0.0008622102,0.0008465562,0.0007557188,0.02410758,0.001194458],"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":[0.00002605419,0.000007123458,0.001218093,0.0002954908,0.00002427341,0.000009353452,0.00002352166,0.0001479707,0.00001309,0.0004749194,0.9956819,0.0020783],"study_design_scores_gemma":[0.0001233852,0.00001049317,0.02088826,0.0007474615,0.00006231766,0.00002725447,0.000444875,0.0004453152,0.0002052187,0.0006140083,0.9763535,0.0000778895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005949123,0.00006159847,0.00002727874,0.0001219057,0.00003096677,0.00001426947,0.9985043,0.0000557048,0.001124512],"genre_scores_gemma":[0.001032595,0.000379945,0.0004282527,0.0001481802,0.0000192252,0.0001106536,0.9924152,0.0001280603,0.005337831],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09476074,"threshold_uncertainty_score":0.3708533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388561201635159,"score_gpt":0.2343035491774609,"score_spread":0.2104179371611093,"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."}}