{"id":"W6957584514","doi":"10.6068/dp14ba8cf1def54","title":"Trend 2001 - 2012. Statistics Canada. CANSIM: Energy - Energy Consumption and Disposition | Country: Canada | Table: Energy fuel consumption of manufacturing industries in gigajoules, by North American Industry Classification System (NAICS) | Variable: Total, energy consumed as fuel (higher heating value), Paint, coating and adhesive manufacturing | Units: Gigajoules, 2001-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-078.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy consumption; Economic statistics; Consumption (sociology); Official statistics; Census; Manufacturing; Descriptive statistics; Energy (signal processing)","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":[0.001738841,0.002391409,0.002633631,0.007527177,0.003197432,0.004381848,0.004983854,0.001482456,0.09216592],"category_scores_gemma":[0.0153292,0.001559429,0.002341753,0.03739814,0.000562781,0.002349954,0.002152974,0.002947857,0.05275865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04316914,"about_ca_system_score_gemma":0.1081911,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934504,"about_ca_topic_score_gemma":0.9916517,"domain_scores_codex":[0.996717,0.000222051,0.0003427324,0.0004559104,0.001476387,0.0007857157],"domain_scores_gemma":[0.9727842,0.0009389473,0.0007389129,0.0008219887,0.02360838,0.001107547],"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":[0.00002550429,0.000006340873,0.001075294,0.0002678529,0.00002452556,0.000007221036,0.00001970962,0.0001277115,0.00000993277,0.0003803716,0.9963545,0.001701059],"study_design_scores_gemma":[0.00016795,0.0000126171,0.02307898,0.000933776,0.00008159212,0.00003086992,0.0004558662,0.0005402606,0.0002042759,0.000727818,0.9736752,0.00009087263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004963663,0.00004688252,0.00002471987,0.0001041359,0.00002552121,0.00001193324,0.9989253,0.00005358203,0.0007582861],"genre_scores_gemma":[0.0007930705,0.0002760839,0.0003592348,0.0001459785,0.00001859185,0.0001088267,0.9947311,0.0001088031,0.003458363],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09216592,"threshold_uncertainty_score":0.3132155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963762323982902,"score_gpt":0.242375141723743,"score_spread":0.212737518483914,"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."}}