{"id":"W6976601571","doi":"10.6068/dp14ba89131eb93","title":"Trend 1983 - 2000. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Average hourly earnings and average weekly hours of employees paid by the hour (SEPH) | Variable: Average hourly earnings, Excluding overtime, Primary metal industries | Units: , 1983-2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Census; Economic statistics; Summary statistics; Wages and salaries; Official statistics; Socioeconomic status; Personal income; Statistical analysis","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":[0.001768144,0.002391759,0.002519107,0.008175272,0.003033311,0.00462652,0.00499163,0.00140683,0.08265203],"category_scores_gemma":[0.01381899,0.001623331,0.001707866,0.03976823,0.0005879754,0.002277696,0.001967048,0.002961784,0.05629227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04792439,"about_ca_system_score_gemma":0.1121938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947225,"about_ca_topic_score_gemma":0.9928497,"domain_scores_codex":[0.9962758,0.0002179395,0.0003462947,0.0004918815,0.001744367,0.0009236808],"domain_scores_gemma":[0.9723974,0.0008848591,0.000911028,0.0007633682,0.02378169,0.001261684],"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":[0.00002389414,0.000007642802,0.001000217,0.000185596,0.0000174486,0.000006778112,0.00001921203,0.0001190768,0.000008388423,0.0003461664,0.9966485,0.001616954],"study_design_scores_gemma":[0.0001527742,0.00001285119,0.02752988,0.0006790383,0.00005496842,0.00002442367,0.0004508689,0.0005405009,0.0002006705,0.0006518174,0.9696154,0.00008691086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006051637,0.00004395699,0.00002255153,0.0000996683,0.00002220247,0.00001223581,0.9988299,0.00006141968,0.0008475761],"genre_scores_gemma":[0.0008569364,0.0002268774,0.0003089372,0.000116411,0.0000157372,0.00008943185,0.9941211,0.00009586186,0.004168677],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08265203,"threshold_uncertainty_score":0.3477174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02109302516661702,"score_gpt":0.2297092099683671,"score_spread":0.2086161848017501,"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."}}