{"id":"W6912974348","doi":"10.5683/sp3/holqgx","title":"Labour Force Survey, October 2023 [Canada] [Rebased 2025]","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"Polymer Foaming and Composites","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Unemployment; Current Population Survey; Official statistics; Population; Wage; Descriptive statistics; Survey data collection; Minimum wage; Public use","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003912909,0.001211418,0.001095046,0.003504552,0.002868331,0.002964394,0.00336711,0.001680667,0.04746068],"category_scores_gemma":[0.01522924,0.001081903,0.001249028,0.008606169,0.0006128501,0.001494365,0.00138056,0.00378754,0.03108525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04592695,"about_ca_system_score_gemma":0.1227595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9863193,"about_ca_topic_score_gemma":0.9897006,"domain_scores_codex":[0.9954745,0.0002765367,0.0003727157,0.0003442325,0.002706296,0.0008256783],"domain_scores_gemma":[0.9814836,0.0003345508,0.0003063191,0.0003081718,0.01654152,0.001025792],"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":[0.0000211829,0.000009754392,0.00120454,0.0001585223,0.000007817778,0.000009525777,0.00003256849,0.00004767452,0.00002063702,0.0004727429,0.9904172,0.007597877],"study_design_scores_gemma":[0.00004768997,0.00001461323,0.06249465,0.0005091534,0.00002484058,0.0000193774,0.0002505572,0.0001200291,0.00005554347,0.0002682956,0.9361622,0.00003296744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008259027,0.002070387,0.0004637516,0.005760267,0.002450129,0.0009659705,0.9345113,0.000335754,0.05261656],"genre_scores_gemma":[0.009888304,0.00578632,0.003718748,0.01008798,0.00050353,0.002402078,0.8263585,0.0003476038,0.140907],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04746068,"threshold_uncertainty_score":0.3332248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02014091548426525,"score_gpt":0.2582145433568629,"score_spread":0.2380736278725976,"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."}}