{"id":"W6958202148","doi":"10.6068/dp15e0092efcf85","title":"Trend 1995 - 2011. Bureau of Labor Statistics. International Labor Statistics [Archive]: Manufacturing Labor Productivity and Unit Labor Costs | Country: Czech Republic | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: REAL HOURLY COMPENSATION, CPI BASIS, PRODUCTIVITY SERIES, 1995-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-031-005.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Particle Accelerators and Free-Electron Lasers","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Unit (ring theory); Currency; National Income and Product Accounts; Liberian dollar; National accounts; Labor cost; Index (typography); Aggregate data","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":[],"category_scores_codex":[0.001026854,0.001256837,0.001527015,0.0003316049,0.0003099449,0.0006087489,0.002631956,0.0008494877,0.002850299],"category_scores_gemma":[0.000142075,0.001297331,0.000003665021,0.00009114817,0.0006739945,0.001813556,0.0009973323,0.001970256,0.0001579108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002387094,"about_ca_system_score_gemma":0.00066837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1126114,"about_ca_topic_score_gemma":0.1273501,"domain_scores_codex":[0.993809,0.0004558785,0.001132606,0.002000789,0.001329858,0.001271823],"domain_scores_gemma":[0.9936664,0.0004848943,0.001205304,0.003806074,0.0001345073,0.0007028535],"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":[0.0005073405,0.0002210411,0.0019646,0.001444244,0.00103649,0.0002575851,0.00002032246,0.00008244521,0.000221879,0.001281245,0.9906621,0.00230071],"study_design_scores_gemma":[0.001297927,0.0002145906,0.02288904,0.0001182597,0.0004433601,0.000156988,0.00007560024,0.002312538,0.00007578896,0.000007715328,0.9711223,0.001285897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009753085,0.0008947936,0.00007155468,0.00005962197,0.0008314181,0.001261133,0.9945264,0.0003822187,0.0009975529],"genre_scores_gemma":[0.002812906,0.003367065,0.002489963,0.00004573878,0.0009135144,0.00006994354,0.9874024,0.0004290307,0.00246942],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02092444,"threshold_uncertainty_score":0.9989476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839281514546835,"score_gpt":0.2672024155317786,"score_spread":0.2388096003863103,"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."}}