{"id":"W6901603188","doi":"10.6068/dp15e0084634d77","title":"Trend 1970 - 2012. Bureau of Labor Statistics. International Labor Statistics [Archive]: Civilian Labor Force, Employment, and Unemployment | Country: Canada | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Whole economy | Series: EMPLOYMENT IN MANUFACTURING, 1970-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-031-001.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Earnings; Unemployment; Current Population Survey; Population; Economic statistics; International comparisons; Wages and salaries; Discouraged worker","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":[0.001942574,0.001988512,0.002573115,0.005419328,0.001792014,0.003466273,0.004276911,0.001247508,0.07372951],"category_scores_gemma":[0.01585712,0.001433921,0.00138659,0.02417456,0.0004356169,0.002403808,0.001772927,0.00343248,0.07058465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01343184,"about_ca_system_score_gemma":0.0338013,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9114282,"about_ca_topic_score_gemma":0.8820128,"domain_scores_codex":[0.9971289,0.0002507486,0.0003456565,0.0004591112,0.001188436,0.0006271321],"domain_scores_gemma":[0.9811695,0.0009037245,0.0008010549,0.0007311437,0.01553717,0.00085733],"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":[0.00002076446,0.000007939629,0.0007639488,0.000145724,0.00001151678,0.00000363098,0.00001598136,0.00006323493,0.000008021016,0.0001973085,0.9974406,0.001321401],"study_design_scores_gemma":[0.0002389702,0.0000188806,0.03573541,0.0008037063,0.0000556078,0.0000248932,0.0004484005,0.0003684346,0.0001651848,0.0006210298,0.9614576,0.00006200275],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005512894,0.0000293838,0.00002877979,0.00006927319,0.00003047388,0.00001904978,0.9991546,0.00005639266,0.0005568421],"genre_scores_gemma":[0.0003911913,0.0001102356,0.0002091787,0.00007447599,0.00001995594,0.0001441359,0.997101,0.0000728802,0.001876816],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08857185,"threshold_uncertainty_score":0.2466498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02835151159440169,"score_gpt":0.2835150337052565,"score_spread":0.2551635221108548,"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."}}