{"id":"W6976444128","doi":"10.6068/dp1549ba448691","title":"Trend 1990 - 2008. United Nations Economic Commission for Europe. Macroeconomic Statistics [Archive]: GDP: Output Approach, in National Currency | Country: Germany | Selection 1: GDP | Selection 2: Millions of NCUs at average prices of 2005, 1990-2008. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 054-001-007.","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commission; Commonwealth; Currency; Economic statistics; Official statistics; National accounts; Economic data; International Standard Industrial Classification","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006997979,0.0004915964,0.0007171543,0.001950986,0.0002326423,0.0001047755,0.00324064,0.000370105,0.0006409797],"category_scores_gemma":[0.00006262877,0.0004847854,0.000002478815,0.0002477614,0.0003547017,0.0004595786,0.001040636,0.0004639664,0.0003530395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003061206,"about_ca_system_score_gemma":0.0004973324,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04131852,"about_ca_topic_score_gemma":0.02328828,"domain_scores_codex":[0.9964945,0.0003024956,0.001114761,0.001169967,0.0004213825,0.0004969146],"domain_scores_gemma":[0.995752,0.001129581,0.001416333,0.001522726,0.0000470404,0.0001323709],"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":[0.00004691247,0.0001798822,0.00001712277,0.0003206548,0.0001034682,0.000003951434,0.000008426889,0.000422118,0.00003459796,0.01499713,0.9833788,0.000486969],"study_design_scores_gemma":[0.0006200854,0.00009922665,0.00002227176,0.00004429449,0.00005027459,0.00005818639,0.000003772699,0.1454637,6.285009e-7,0.00001436922,0.8532105,0.0004127338],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001807655,0.0003775195,0.01426,0.00001192362,0.0004524188,0.0007281513,0.9791425,0.0002361983,0.004789488],"genre_scores_gemma":[0.00006610782,0.0009098568,0.02184216,0.00001255755,0.0001152032,0.00003100524,0.9737607,0.00009400573,0.003168415],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1450416,"threshold_uncertainty_score":0.9997604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03352392405892184,"score_gpt":0.2775833588251005,"score_spread":0.2440594347661787,"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."}}