{"id":"W6931744129","doi":"10.5683/sp3/bnsn4y","title":"Labour Force Survey, March 2016 [Canada] [Rebased 2025]","year":2016,"lang":"en","type":"dataset","venue":"Borealis","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Current Population Survey; Government (linguistics); Population; Wage; Descriptive statistics; Minimum wage; Discouraged worker","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":[0.0008688942,0.0003833594,0.0004353794,0.0002090656,0.0001783864,0.0002044745,0.003012892,0.0002764508,0.00007126],"category_scores_gemma":[0.0002824508,0.0003084676,0.00008873981,0.0003427475,0.00005214689,0.0001622038,0.0006739453,0.0002859815,0.00002236887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002024998,"about_ca_system_score_gemma":0.001651881,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8937867,"about_ca_topic_score_gemma":0.7846563,"domain_scores_codex":[0.9972129,0.0004078044,0.000447923,0.0007332134,0.0006486028,0.0005495271],"domain_scores_gemma":[0.9966714,0.000448108,0.0003242822,0.002018297,0.000331065,0.0002068825],"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":[0.000005796262,0.00001855,0.00001082078,0.00002747161,0.00002347921,0.00002849394,0.000001932858,0.00002379742,5.028786e-7,0.0002944834,0.9983633,0.001201399],"study_design_scores_gemma":[0.0001904992,0.00003663959,0.000911472,0.0001095917,0.000006596167,0.000005630124,2.841677e-7,0.0006115973,0.00003258184,0.0003142559,0.9973421,0.0004387514],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[2.389336e-7,0.0001337822,0.1821953,0.0006677048,0.0002955702,0.0001864104,0.8157951,0.0002270904,0.0004988415],"genre_scores_gemma":[0.000005505215,0.0004515419,0.006783346,0.001177464,0.0002032114,0.00002995777,0.9879578,0.00002172946,0.003369496],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.175412,"threshold_uncertainty_score":0.9999368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01984059220498157,"score_gpt":0.2687347735150934,"score_spread":0.2488941813101118,"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."}}