{"id":"W6976728031","doi":"10.6068/dp15e737ca2b375","title":"Trend 2013 - 2014. Energy Information Administration. International Energy Statistics: Coal | Country: Canada | Category: Imports | Series: Metallurgical Coal Imports | Units: Btu, 2013-2014. 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":"Coal; Administration (probate law); Agency (philosophy); Energy (signal processing); Energy policy; CONQUEST; Production (economics); International comparisons","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":[0.001515165,0.001875144,0.002280084,0.00636042,0.001925746,0.004637664,0.003691653,0.001324613,0.07444169],"category_scores_gemma":[0.0130445,0.00131696,0.00148408,0.03119629,0.0005928981,0.002825787,0.001905195,0.003028981,0.07001117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01753134,"about_ca_system_score_gemma":0.04031474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9223754,"about_ca_topic_score_gemma":0.9155814,"domain_scores_codex":[0.9975685,0.0001622042,0.0002472311,0.0003582474,0.001150078,0.0005136656],"domain_scores_gemma":[0.9827992,0.0008202557,0.000657359,0.0009397258,0.01403454,0.0007488472],"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":[0.00001715047,0.000005785255,0.0004581273,0.0001461679,0.00001314734,0.000003659134,0.00000908142,0.00009310049,0.000009696447,0.0002919164,0.9979857,0.0009664431],"study_design_scores_gemma":[0.00008905583,0.000006707382,0.008996272,0.0004299702,0.00002745574,0.00001146963,0.0001958607,0.0003268873,0.0001873306,0.0007049352,0.9889816,0.00004258589],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003029698,0.00002153633,0.00001699892,0.00005546001,0.00001836865,0.000006934918,0.9992738,0.00005463461,0.000521882],"genre_scores_gemma":[0.0002275446,0.00007035778,0.0001326615,0.00004092864,0.000008099826,0.00004392913,0.9982023,0.0000532923,0.00122083],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07762456,"threshold_uncertainty_score":0.2490323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02186005398460743,"score_gpt":0.2587267989879384,"score_spread":0.236866745003331,"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."}}