{"id":"W6920597004","doi":"10.6068/dp15df2d44d6590","title":"Trend 1990 - 2014. Energy Information Administration. International Energy Statistics: Natural Gas | Country: Canada | Category: Imports | Series: Imports of Dry Natural Gas | Units: Cubic Feet, 1990-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 004-015-005.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural gas; Energy policy; Energy (signal processing); Agency (philosophy); Administration (probate law); Production (economics); Natural resource; Environmental impact of the energy industry","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":[0.001220632,0.001869802,0.00207922,0.006545249,0.001505009,0.003806448,0.00331716,0.001153105,0.05066104],"category_scores_gemma":[0.01030748,0.001289913,0.001411026,0.03002851,0.000511864,0.00260859,0.001641688,0.002949449,0.05099094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01535371,"about_ca_system_score_gemma":0.03284986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9125132,"about_ca_topic_score_gemma":0.8916896,"domain_scores_codex":[0.9977818,0.0001318157,0.0002377442,0.0003387801,0.00108332,0.000426477],"domain_scores_gemma":[0.9850962,0.0006313621,0.0006512114,0.0006857061,0.01241041,0.0005251944],"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":[0.00002100598,0.00000820913,0.0008472661,0.0002236775,0.00001965984,0.000005380451,0.00001156519,0.0001405754,0.00001393832,0.000392579,0.9970715,0.001244759],"study_design_scores_gemma":[0.00009940741,0.00000913148,0.01566689,0.0004934648,0.00003605472,0.00001586516,0.0002094432,0.0003715868,0.0002228582,0.0006400941,0.9821922,0.00004305878],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004296473,0.00002769465,0.00001469342,0.00004167538,0.00001714806,0.00000651444,0.9993069,0.00004121972,0.0005011695],"genre_scores_gemma":[0.0002860116,0.00007483833,0.0001090973,0.00002877422,0.000007100145,0.00003559056,0.998442,0.00003518668,0.000981422],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0874868,"threshold_uncertainty_score":0.176004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01417331540434065,"score_gpt":0.2494965903858676,"score_spread":0.235323274981527,"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."}}