{"id":"W6906696138","doi":"10.18164/906590d1-0915-4f67-9045-19e21178c85b","title":"Data collected under the Fuels Information Regulations, No. 1","year":2017,"lang":"en","type":"dataset","venue":"ECCC Data Catalogue","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Environment and Climate Change Canada","funders":"","keywords":"Coal; Production (economics); Climate change; Fossil fuel; Asphalt; Data collection","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001651108,0.001645254,0.001351251,0.004384888,0.001075513,0.002599126,0.002128822,0.00169252,0.06162982],"category_scores_gemma":[0.00895537,0.0006776297,0.001064687,0.01165075,0.000554347,0.001566529,0.002000215,0.00206712,0.1081232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002250995,"about_ca_system_score_gemma":0.005471378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04674695,"about_ca_topic_score_gemma":0.06218171,"domain_scores_codex":[0.9975474,0.0003385947,0.0003405265,0.000602762,0.0008106225,0.0003599631],"domain_scores_gemma":[0.9959745,0.0008702785,0.0004611601,0.0007784471,0.001624027,0.0002916403],"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":[0.00002903601,0.00001515162,0.0006679239,0.0002722521,0.00001148596,0.00001038736,0.00002145302,0.0001368451,0.00004854972,0.0007469432,0.9964883,0.001551562],"study_design_scores_gemma":[0.0000617078,0.000007501343,0.002579388,0.0002462296,0.00001351788,0.00001976531,0.00008524298,0.0001175691,0.0001509114,0.0008957719,0.995805,0.00001728229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008358041,0.00003069171,0.00005065199,0.00003704662,0.00001876977,0.00001337455,0.9989511,0.00007399886,0.0007407134],"genre_scores_gemma":[0.0001714043,0.00004079709,0.0001337152,0.00002479238,0.000004268688,0.00008353013,0.9987549,0.00003363548,0.0007529784],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06162982,"threshold_uncertainty_score":0.2061723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09113786581540269,"score_gpt":0.3384985791209802,"score_spread":0.2473607133055776,"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."}}