{"id":"W6976246658","doi":"10.6068/dp14ba8b44fd412","title":"Trend 2001 - 2012. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Average weekly earnings (SEPH), by type of employee for selected industries classified using the North American Industry Classification System (NAICS) | Variable: Employees paid by the hour, Arts, entertainment and recreation, Excluding overtime | Units: Current $CAD, 2001-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Overtime; Census; Economic statistics; Wages and salaries; Summary statistics; Official statistics; Socioeconomic status; Descriptive statistics","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":[0.001680404,0.002630579,0.002697054,0.007750547,0.002824605,0.004553176,0.005264332,0.00148701,0.07229199],"category_scores_gemma":[0.01428741,0.00162428,0.001958001,0.03759055,0.0005746884,0.002245616,0.002009709,0.003131869,0.05586265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03980868,"about_ca_system_score_gemma":0.09484142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921179,"about_ca_topic_score_gemma":0.9908093,"domain_scores_codex":[0.9964999,0.0002073128,0.0003399772,0.0005025477,0.001586049,0.0008642697],"domain_scores_gemma":[0.9712582,0.0009434246,0.0009903403,0.0008528022,0.02466082,0.001294435],"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":[0.00002666248,0.000007413647,0.001132304,0.0001793514,0.0000191629,0.000005917731,0.00001407466,0.0001118815,0.000008273338,0.0002208456,0.9970425,0.001231708],"study_design_scores_gemma":[0.0002238847,0.00001549163,0.03220803,0.0008074932,0.00006809135,0.00002775209,0.0004425869,0.0006462595,0.0002240412,0.0005876131,0.9646534,0.00009540586],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000553422,0.00003760534,0.00001495837,0.00008291835,0.00002039313,0.000008941033,0.9991911,0.00004873468,0.0005399698],"genre_scores_gemma":[0.0005556758,0.0001493101,0.0001776295,0.00008515679,0.00001344293,0.00006003408,0.9965224,0.00006119824,0.002375201],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07229199,"threshold_uncertainty_score":0.2888335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05347516366912171,"score_gpt":0.2764403642952088,"score_spread":0.2229652006260871,"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."}}