{"id":"W6976193959","doi":"10.6068/dp15e6e7e8a7133","title":"Trend 1980 - 2014. Energy Information Administration. International Energy Statistics: Coal | Country: Canada | Category: Imports | Series: Primary Coal Imports | 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":"Tonne; Coal; Energy policy; Administration (probate law); Energy (signal processing); Agency (philosophy); Production (economics); Primary energy","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":[0.001241308,0.001875175,0.002111273,0.007062561,0.001776368,0.003949422,0.003417849,0.001182095,0.05277395],"category_scores_gemma":[0.01104711,0.0012964,0.001383778,0.03177014,0.000559432,0.002647297,0.001694131,0.002936847,0.052716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01783266,"about_ca_system_score_gemma":0.0405108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9316344,"about_ca_topic_score_gemma":0.920424,"domain_scores_codex":[0.9977284,0.000126397,0.0002282627,0.0003297674,0.001107053,0.00048006],"domain_scores_gemma":[0.983358,0.0006470892,0.0006539505,0.0007209912,0.01400181,0.000618096],"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":[0.00001961392,0.000007608206,0.0007724514,0.000199393,0.00001873089,0.000005267241,0.00001167968,0.0001202907,0.00001361571,0.0003775498,0.9972575,0.001196345],"study_design_scores_gemma":[0.00008849778,0.000008163202,0.01423045,0.0004659702,0.00003578431,0.00001443315,0.0002164726,0.0003029152,0.000213152,0.000584062,0.983798,0.00004205803],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004556779,0.0000291287,0.00001402642,0.00004768824,0.0000187912,0.000006449403,0.9992507,0.00004285461,0.0005446934],"genre_scores_gemma":[0.0002840074,0.00007739971,0.0001020525,0.00003020282,0.000007355592,0.00003468194,0.9982673,0.0000360156,0.001160977],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06836557,"threshold_uncertainty_score":0.1765465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386486924523635,"score_gpt":0.2639439087386652,"score_spread":0.2400790394934288,"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."}}