{"id":"W6920452361","doi":"10.6068/dp150a25d169e35","title":"Map of Countries (2006). United Nations Economic Commission for Europe. Gender Statistics [Archive]: Time Use by Activity | Selection 1: All activities | Selection 2: Both sexes, 2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 054-003-066.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commission; Official statistics; Time-use survey; Selection (genetic algorithm); National accounts; Data collection; Economic statistics; Economic data; Social 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001178781,0.001038227,0.001268934,0.001285068,0.0003244966,0.000573948,0.00172782,0.0007088383,0.007678899],"category_scores_gemma":[0.0001167191,0.001092641,0.000001836559,0.0001923645,0.0005119247,0.001425257,0.0006811,0.0009441846,0.006525553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003581982,"about_ca_system_score_gemma":0.00115467,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3448976,"about_ca_topic_score_gemma":0.05697079,"domain_scores_codex":[0.9941836,0.001414888,0.001028068,0.001636383,0.0008602231,0.0008768156],"domain_scores_gemma":[0.992828,0.002462221,0.001770687,0.00240263,0.0001001154,0.0004363474],"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":[0.0009568065,0.0003848218,0.00002096502,0.0008377543,0.0008352664,0.00001077121,0.000009263509,0.0001429548,0.0006435058,0.000798898,0.9953246,0.00003436393],"study_design_scores_gemma":[0.001093639,0.000290035,0.000005254619,0.0000340618,0.0008401829,0.00007970855,0.00002757496,0.04279584,0.000003637314,0.000001771039,0.9537985,0.001029811],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000126306,0.0002811277,0.0008094838,0.000004149867,0.0003539659,0.001739384,0.9935272,0.0004659219,0.0028175],"genre_scores_gemma":[0.000009690893,0.0005241928,0.002438176,0.00003160381,0.0002722895,0.0000527338,0.9715543,0.0008128819,0.02430408],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2879268,"threshold_uncertainty_score":0.9991524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06165362865924735,"score_gpt":0.3019323426279569,"score_spread":0.2402787139687095,"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."}}