{"id":"W6957678334","doi":"10.6068/dp14ba88b1b8433","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour force survey estimates (LFS), weekly wage distributions of employees by type of work, North American Industry Classification System (NAICS), and sex | Variable: Services-producing sector, Males, Part-time employees, $500 to $799 | Units: # Persons x 1,000, 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; Wage; Census; Economic statistics; Summary statistics; Wages and salaries; Socioeconomic status; Official statistics; Distribution (mathematics)","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":[0.002070662,0.002427427,0.00297239,0.007723254,0.002967704,0.004303483,0.005505926,0.0014349,0.08519209],"category_scores_gemma":[0.01563644,0.001809983,0.002163572,0.03842622,0.0005588761,0.002196096,0.002181523,0.003317365,0.05395051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04587485,"about_ca_system_score_gemma":0.1152932,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941252,"about_ca_topic_score_gemma":0.9922473,"domain_scores_codex":[0.9958193,0.0002627766,0.0004462871,0.0005111373,0.001972032,0.0009885094],"domain_scores_gemma":[0.9683612,0.001002384,0.001014714,0.000805809,0.02736762,0.001448347],"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":[0.00002930851,0.000008396949,0.001154807,0.000235973,0.00002394257,0.000006072097,0.00001841983,0.00009913911,0.000007952179,0.0002622836,0.9964435,0.001710219],"study_design_scores_gemma":[0.0002701025,0.00002038369,0.04177205,0.001115873,0.0000977919,0.00003258333,0.0005675531,0.0005999171,0.0002056551,0.0007197683,0.9544936,0.0001047238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000069436,0.0000523233,0.00002295213,0.0001128415,0.00003066315,0.00001618446,0.9988493,0.00005413052,0.0007920495],"genre_scores_gemma":[0.0008062513,0.0002527108,0.0002959201,0.000161005,0.00001964537,0.0001174456,0.9941223,0.00008591849,0.004138796],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08519209,"threshold_uncertainty_score":0.3328469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03052623992602326,"score_gpt":0.2504435403412323,"score_spread":0.219917300415209,"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."}}