{"id":"W6976879195","doi":"10.6068/dp15e0075a7b164","title":"Trend 1996 - 2011. Bureau of Labor Statistics. International Labor Statistics [Archive]: Hourly Compensation of Manufacturing Workers | Country: Canada | Seasonally Adjusted: Non-Seasonally Adjusted | Industry: Manufacturing | Series: MANUFACTURING HR SOCIAL INSURANCE AND LABOR TAXES, U.S. DOLLARS, 1996-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-031-004.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Payroll; Compensation of employees; Wage; Production (economics); Manufacturing; Guard (computer science); Wages and salaries; Apprenticeship; Census","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":[0.001689694,0.002006756,0.002267165,0.005606479,0.001644158,0.003700941,0.003934277,0.001449534,0.06522302],"category_scores_gemma":[0.0143452,0.00128866,0.00141683,0.02414063,0.0004258225,0.002205778,0.001691438,0.003262108,0.07641413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01163958,"about_ca_system_score_gemma":0.02454093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8452495,"about_ca_topic_score_gemma":0.8045498,"domain_scores_codex":[0.9970672,0.000229343,0.0003797891,0.0005289026,0.0012067,0.0005882535],"domain_scores_gemma":[0.9836357,0.0008445927,0.0008866864,0.000835053,0.01311685,0.0006810215],"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":[0.00001804438,0.000007213518,0.0007087474,0.0001355472,0.00001198832,0.00000404269,0.000009333961,0.0000668775,0.000006950344,0.0001843814,0.9978471,0.0009998388],"study_design_scores_gemma":[0.0001589679,0.0000132556,0.02129194,0.0006660658,0.00004432715,0.00002189319,0.0002927146,0.0002894286,0.0001392238,0.0005464388,0.9764878,0.00004798537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004027548,0.0000285031,0.00001539106,0.00006080645,0.00002354907,0.000007925683,0.9993942,0.00003143626,0.0003979648],"genre_scores_gemma":[0.0002700144,0.00008311325,0.0001091668,0.00005157623,0.00001291229,0.00005852166,0.9982327,0.00003311539,0.001148839],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1547505,"threshold_uncertainty_score":0.3113236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880115514800628,"score_gpt":0.2733976564319651,"score_spread":0.2445965012839588,"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."}}