{"id":"W6957603504","doi":"10.6068/dp15410dd340232","title":"Most Recent Data (2008). United Nations Economic Commission for Europe. Gender Statistics [Archive]: Youth Unemployment | Country: Hungary | Selection 1: Both sexes | Selection 2: Young unemployed persons | Selection 3: , 2008. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 054-003-028.","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commission; Unemployment; Commonwealth; Official statistics; Selection (genetic algorithm); Youth unemployment; Per capita; Economic statistics","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":[0.001717896,0.001536096,0.001667216,0.004270059,0.0008807875,0.002926744,0.002213881,0.001131285,0.1282149],"category_scores_gemma":[0.01441959,0.001059572,0.001026843,0.01730647,0.0002873829,0.002616691,0.002058954,0.002227861,0.1310826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002690543,"about_ca_system_score_gemma":0.004500953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09497413,"about_ca_topic_score_gemma":0.0610252,"domain_scores_codex":[0.9978231,0.0002636262,0.0003490435,0.0003678609,0.0007954663,0.0004009757],"domain_scores_gemma":[0.9916992,0.00125841,0.0007638248,0.0005675198,0.005275765,0.0004352585],"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":[0.00001971609,0.00000667085,0.0004613637,0.0001869949,0.000006286677,0.00000464045,0.00001166936,0.00002899338,0.000009898569,0.0001916288,0.9978733,0.001198835],"study_design_scores_gemma":[0.000123181,0.00001477773,0.01661938,0.0005690583,0.00002230779,0.00002157852,0.0002234826,0.000078656,0.0001161384,0.000477446,0.9817086,0.00002525447],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000559221,0.00003028642,0.00001875419,0.00006254747,0.0000389591,0.0000107178,0.9989523,0.00003767272,0.0007929134],"genre_scores_gemma":[0.0003867043,0.00009913721,0.0001909674,0.00008577271,0.00002101261,0.0001466922,0.9968169,0.00006629284,0.002186569],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1282149,"threshold_uncertainty_score":0.4289216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06405830098963547,"score_gpt":0.3060642115856794,"score_spread":0.242005910596044,"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."}}