{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003990405,0.001250292,0.001326611,0.004189841,0.003136231,0.003029821,0.003749602,0.001371416,0.04017394],"category_scores_gemma":[0.01851522,0.001136943,0.001369841,0.01142729,0.0006363595,0.001699903,0.001558848,0.003636555,0.02331742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05247309,"about_ca_system_score_gemma":0.1326988,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892847,"about_ca_topic_score_gemma":0.9921041,"domain_scores_codex":[0.9945613,0.0003034283,0.0004959255,0.0004309679,0.003324805,0.0008836033],"domain_scores_gemma":[0.9765854,0.0003747678,0.0004068069,0.0003760487,0.02117998,0.001077117],"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":[0.0000276645,0.00001162311,0.001964966,0.0002650552,0.00001189506,0.00001113584,0.00005378083,0.00006080878,0.0000219985,0.00051142,0.9892386,0.007821037],"study_design_scores_gemma":[0.00007244363,0.00001795347,0.09583791,0.0008293951,0.00003811822,0.00002556506,0.0004365958,0.0001604381,0.00007415396,0.000351223,0.9021057,0.00005039793],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007414007,0.001177047,0.0002913115,0.00301804,0.001347723,0.0007672081,0.965519,0.0002270659,0.02691133],"genre_scores_gemma":[0.008093717,0.004528814,0.002869863,0.005603716,0.0003521809,0.002391464,0.9044255,0.0002560942,0.07147873],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05247309,"threshold_uncertainty_score":0.3807207,"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."}}