{"id":"W6907872700","doi":"10.25318/9810045401-eng","title":"Occupation (STEM and non-STEM) by visible minority, generation status, age and gender: Canada, provinces and territories, census metropolitan areas and census agglomerations with parts","year":2022,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Urban agglomeration; American Community Survey; Population","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":[0.0008842511,0.001594513,0.001492634,0.004371519,0.001789668,0.002440208,0.004016147,0.001286068,0.04297321],"category_scores_gemma":[0.006231214,0.001052113,0.001231446,0.01630802,0.0005026119,0.001040121,0.001519893,0.002278955,0.02288899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01320887,"about_ca_system_score_gemma":0.02985919,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9551083,"about_ca_topic_score_gemma":0.9709237,"domain_scores_codex":[0.9986731,0.00007978654,0.0001259857,0.0002252212,0.0004510617,0.0004449332],"domain_scores_gemma":[0.9940823,0.0003821566,0.0004796939,0.0003902522,0.003968382,0.0006972986],"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":[0.0000350106,0.00001521418,0.003239623,0.0002882546,0.00002723572,0.00001380846,0.00004191619,0.0001676373,0.00001961384,0.0004259406,0.9945963,0.001129406],"study_design_scores_gemma":[0.0003202295,0.00001585994,0.09431442,0.0008369095,0.00007993217,0.000076775,0.0006407677,0.0004966797,0.0002936196,0.0007353346,0.9021203,0.0000693193],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001879252,0.00002980707,0.00001787881,0.00003060369,0.000009292503,0.000009668038,0.9992889,0.0000223496,0.0004035078],"genre_scores_gemma":[0.001381764,0.000078464,0.0001642622,0.0000470931,0.00000578663,0.00008719457,0.9963368,0.00002464303,0.001873953],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04489172,"threshold_uncertainty_score":0.1437597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239345769103457,"score_gpt":0.2546420110934658,"score_spread":0.2422485534024312,"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."}}