{"id":"W6920433038","doi":"10.6068/dp14ba8d632853","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: 15 years and over, Health care and social assistance, Both sexes, Full-time, 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; Survey data collection","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":[0.002159736,0.002530884,0.003092553,0.007683661,0.002918042,0.004636262,0.005531379,0.001527556,0.09048665],"category_scores_gemma":[0.01691187,0.001938305,0.00226718,0.03876114,0.0005739258,0.002282612,0.002272998,0.003419393,0.05701976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04701737,"about_ca_system_score_gemma":0.1160487,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940627,"about_ca_topic_score_gemma":0.9921886,"domain_scores_codex":[0.9957491,0.0002916332,0.0004825896,0.0005210221,0.001947924,0.001007676],"domain_scores_gemma":[0.9674783,0.001131508,0.001051891,0.0008519554,0.02794476,0.001541404],"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":[0.0000298331,0.000008685273,0.001017382,0.000247732,0.00002401754,0.000005968373,0.00001871169,0.000101514,0.000007769756,0.000267984,0.9966406,0.00162993],"study_design_scores_gemma":[0.0002940191,0.00002032556,0.03662264,0.001182827,0.00009728601,0.00003220991,0.0005385504,0.0006095535,0.0001997234,0.0007674632,0.9595246,0.0001108771],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000601977,0.00005145757,0.00002282793,0.000109177,0.00002980068,0.00001694316,0.9988764,0.00005571526,0.0007774387],"genre_scores_gemma":[0.0007527433,0.0002597117,0.0003108754,0.0001650518,0.00001982979,0.0001252726,0.9943911,0.0000945716,0.003880739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09048665,"threshold_uncertainty_score":0.3411365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02456120679647389,"score_gpt":0.2631533904304925,"score_spread":0.2385921836340186,"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."}}