{"id":"W6888982176","doi":"10.25318/1410025601-eng","title":"Average weekly earnings (SEPH), including overtime, seasonally adjusted, for all employees, by selected industries classified using the North American Industry Classification System (NAICS)","year":2020,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Table (database); Aggregate (composite); Census; Aggregate data","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003662049,0.0006400956,0.0006250051,0.0001970339,0.000609825,0.0006355999,0.002183303,0.0004348311,0.000004772012],"category_scores_gemma":[0.001960525,0.0006271208,0.00004264624,0.00182357,0.0001677724,0.000381189,0.000498681,0.001543427,0.000002384824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001951303,"about_ca_system_score_gemma":0.002835576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0640806,"about_ca_topic_score_gemma":0.1946435,"domain_scores_codex":[0.9957856,0.0003205826,0.0008692433,0.00105468,0.001307904,0.0006619821],"domain_scores_gemma":[0.9948139,0.001196961,0.00175661,0.001030451,0.0009053197,0.0002967415],"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":[0.000020847,0.00003292989,0.0004907695,0.0002272063,0.0001158907,0.00002205331,0.00009039509,0.0000268933,0.000090973,0.0004459087,0.9953628,0.003073401],"study_design_scores_gemma":[0.0003646706,0.0004021658,0.01842917,0.000604069,0.000435954,0.00003715083,0.0008120874,0.06992275,0.0004490785,0.00002084368,0.9069203,0.00160184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005631703,0.00001617932,0.2352303,0.0004212069,0.0002510831,0.0008114555,0.7624843,0.0002167496,0.000005578174],"genre_scores_gemma":[0.02061589,0.00002306041,0.01950571,0.0002682917,0.0001438664,0.0002211098,0.9590898,0.00006987931,0.00006241539],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2157246,"threshold_uncertainty_score":0.999618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03267405714772104,"score_gpt":0.2877080572489528,"score_spread":0.2550340001012318,"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."}}