{"id":"W6889064522","doi":"10.25318/1410045701-eng","title":"Small area estimates of labour force characteristics for sub-provincial areas, monthly, unadjusted for seasonality","year":2025,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada","funders":"","keywords":"Census; Seasonality; Metropolitan area; Unemployment; Urban agglomeration; Seasonal adjustment","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001384157,0.001436082,0.001310173,0.004280344,0.001092486,0.001629421,0.003054445,0.0007613973,0.04662083],"category_scores_gemma":[0.01008598,0.001125624,0.001586809,0.01510772,0.0003342002,0.0009551215,0.001380419,0.001621753,0.01833147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009281886,"about_ca_system_score_gemma":0.02114713,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9250771,"about_ca_topic_score_gemma":0.9468222,"domain_scores_codex":[0.9981593,0.0001458393,0.0002465407,0.0003376104,0.0006764625,0.0004341528],"domain_scores_gemma":[0.9918932,0.0005090663,0.0007281007,0.0005866303,0.005798431,0.0004845832],"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":[0.00006236113,0.00001549025,0.006342676,0.000516063,0.00006576625,0.00001548664,0.00004482996,0.000300712,0.0000479852,0.0005777017,0.9894308,0.002580095],"study_design_scores_gemma":[0.0004157258,0.00002726561,0.189467,0.0008961165,0.0001390783,0.00007413203,0.0003606079,0.001157122,0.0003974942,0.0007337651,0.8062643,0.00006738054],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002702172,0.00003966758,0.00006126055,0.00003046836,0.00001394403,0.00002135093,0.9988775,0.00004098301,0.0006446961],"genre_scores_gemma":[0.002284287,0.000102168,0.0004471328,0.0000425572,0.000008407547,0.0001769816,0.9934959,0.000046029,0.003396566],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07492286,"threshold_uncertainty_score":0.1559622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411946960595546,"score_gpt":0.272145045968967,"score_spread":0.2580255763630115,"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."}}