{"id":"W6901632928","doi":"10.6068/dp15e736c2dd683","title":"Trend 1980 - 2014. Energy Information Administration. International Energy Statistics: Coal | Country: Canada | Category: Production | Series: Metallurgical Coke Production | Units: Metric Tons of Oil Equivalent, 1980-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 004-015-002.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Tonne; Coal; Agency (philosophy); Energy policy; Energy (signal processing); Administration (probate law); Coal mining","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":[0.001279237,0.001976157,0.002238183,0.007219039,0.001831403,0.004302682,0.003505392,0.001244892,0.05661225],"category_scores_gemma":[0.0113329,0.001385039,0.001362294,0.03380745,0.0005928939,0.002772596,0.001775904,0.003042069,0.05562099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01874848,"about_ca_system_score_gemma":0.04285132,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.932176,"about_ca_topic_score_gemma":0.9183144,"domain_scores_codex":[0.9975898,0.0001317302,0.00024116,0.0003465183,0.001197773,0.0004930397],"domain_scores_gemma":[0.9826247,0.0006985323,0.0006881513,0.0007785419,0.01454104,0.0006690506],"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":[0.00001932793,0.000007654365,0.0007245694,0.0001995698,0.00001823743,0.000005041222,0.00001080724,0.0001248617,0.00001315087,0.0003638488,0.9973474,0.001165576],"study_design_scores_gemma":[0.00008931492,0.000007787828,0.01316269,0.0004419382,0.00003315723,0.00001318955,0.0002128355,0.0003016076,0.0002119946,0.0005738382,0.9849091,0.00004253508],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004222422,0.00002827931,0.00001347386,0.00004949187,0.00001895657,0.000006274167,0.9992669,0.00004136238,0.0005329455],"genre_scores_gemma":[0.0002810143,0.00008573091,0.00009732333,0.00003054262,0.000008132681,0.00003691424,0.9981705,0.00003822065,0.001251521],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06782401,"threshold_uncertainty_score":0.1893868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03289162612017948,"score_gpt":0.2723866370902105,"score_spread":0.2394950109700311,"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."}}