{"id":"W6920602221","doi":"10.6068/dp14ba8e116d850","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour force survey estimates (LFS), wages of employees by type of work, North American Industry Classification System (NAICS), sex and age group | Variable: 25 to 54 years, Finance, insurance, real estate and leasing, Males, Total employees, Average weekly wage rate | Units: Current $CAD, 1997-2013. 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; Wage; Wages and salaries; Summary statistics; Socioeconomic status; Official statistics; Immigration","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":[0.001994843,0.002511768,0.003007788,0.007664155,0.003039934,0.004660533,0.005338681,0.00153629,0.09181624],"category_scores_gemma":[0.01590062,0.001878569,0.002133576,0.03945135,0.0005793544,0.002281765,0.002229842,0.003336248,0.06129926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0447077,"about_ca_system_score_gemma":0.1113935,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938291,"about_ca_topic_score_gemma":0.9920657,"domain_scores_codex":[0.9959685,0.0002564009,0.0004351945,0.0005096997,0.001848768,0.000981539],"domain_scores_gemma":[0.9677184,0.001099142,0.001014683,0.0008603835,0.02777879,0.001528489],"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":[0.00002708602,0.000008064885,0.0009626228,0.0002177258,0.00002014441,0.000005662279,0.00001755762,0.00009122912,0.00000750475,0.0002322975,0.9969302,0.001479862],"study_design_scores_gemma":[0.0002701661,0.00001902266,0.03550945,0.001071788,0.00008548095,0.00003039204,0.000545909,0.0005775197,0.0001963542,0.0006934097,0.9608977,0.0001028038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005661847,0.00004437055,0.00001962842,0.0001001925,0.00002746492,0.00001415321,0.9989815,0.00005158337,0.0007043433],"genre_scores_gemma":[0.00066535,0.0002156195,0.0002574868,0.0001411343,0.0000178206,0.0001045577,0.9949608,0.00008437955,0.003552803],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09181624,"threshold_uncertainty_score":0.3243786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692154093385226,"score_gpt":0.2549094130324993,"score_spread":0.227987872098647,"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."}}