{"id":"W6976775162","doi":"10.6068/dp15df2dcb50a50","title":"Trend 2013 - 2014. Energy Information Administration. International Energy Statistics: Coal | Country: Canada | Category: Imports | Series: Metallurgical Coal 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":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coal; Administration (probate law); Agency (philosophy); Energy policy; Energy (signal processing); Production (economics); International comparisons; 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":[0.00142752,0.001878747,0.002251079,0.006195908,0.001898258,0.004464947,0.003659088,0.001308439,0.06927866],"category_scores_gemma":[0.01199229,0.001299815,0.001489808,0.0301901,0.0005873809,0.002749074,0.001855139,0.002979842,0.0660729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01762655,"about_ca_system_score_gemma":0.0395413,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9268566,"about_ca_topic_score_gemma":0.9199716,"domain_scores_codex":[0.9976785,0.0001496513,0.0002314993,0.000347512,0.001101824,0.0004912098],"domain_scores_gemma":[0.9837962,0.0007293594,0.0006058796,0.0008529621,0.01331334,0.0007022379],"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":[0.00001842521,0.00000628587,0.0005014372,0.0001531089,0.0000140362,0.000003950401,0.000009336845,0.000100806,0.00001072608,0.0002926253,0.9978936,0.0009957127],"study_design_scores_gemma":[0.00009211335,0.000006987577,0.00957957,0.0004285655,0.00002837945,0.00001191748,0.0002026588,0.0003540612,0.0002042274,0.0006892165,0.9883585,0.00004376091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003234445,0.00002132895,0.00001643084,0.00005226423,0.00001799484,0.000006783846,0.999292,0.00005324217,0.0005075185],"genre_scores_gemma":[0.0002306072,0.00006771123,0.0001270781,0.00003869887,0.000007705124,0.00004019432,0.9982796,0.00004879835,0.001159653],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07314336,"threshold_uncertainty_score":0.2317602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0527561649323995,"score_gpt":0.3195157041728939,"score_spread":0.2667595392404944,"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."}}