{"id":"W6957735557","doi":"10.6068/dp15df2edbb4c10","title":"Trend 2013 - 2014. Energy Information Administration. International Energy Statistics: Coal | Country: Canada | Category: Imports | Series: Subbituminous Imports | Units: Short Tons, 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":"Epilepsy research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Administration (probate law); Coal; Energy policy; Agency (philosophy); Energy (signal processing); Production (economics); CONQUEST; 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":[0.001378301,0.001875179,0.002143422,0.006363887,0.001817577,0.004282783,0.003584752,0.001237576,0.06521039],"category_scores_gemma":[0.01121595,0.001302895,0.001482015,0.03041904,0.0005615384,0.002710222,0.001765465,0.002955058,0.06006755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01771029,"about_ca_system_score_gemma":0.03927239,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9304475,"about_ca_topic_score_gemma":0.9211338,"domain_scores_codex":[0.9977565,0.0001363412,0.0002179338,0.0003251632,0.001091497,0.0004725861],"domain_scores_gemma":[0.984349,0.0006690584,0.0005831915,0.000765373,0.01298891,0.0006445164],"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":[0.00002001937,0.000006875157,0.000571668,0.000163508,0.00001508059,0.000004327919,0.000009802219,0.0001107465,0.00001198428,0.0003207473,0.9976835,0.00108175],"study_design_scores_gemma":[0.000091996,0.000007264173,0.01089697,0.0004159661,0.00002941093,0.00001320378,0.000204443,0.0003724119,0.0002252215,0.0006707213,0.9870279,0.00004436629],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003626366,0.00002245627,0.00001699164,0.00005040692,0.00001796935,0.000006793133,0.9992592,0.0000540496,0.0005358916],"genre_scores_gemma":[0.0002481685,0.00006841819,0.0001279806,0.0000352438,0.000007408506,0.00003725048,0.9982503,0.00004740948,0.001177818],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06955254,"threshold_uncertainty_score":0.2181506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02398719241118188,"score_gpt":0.282622791092092,"score_spread":0.2586355986809102,"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."}}