{"id":"W6889018442","doi":"10.25318/9810032801-eng","title":"Shelter-cost-to-income ratio by visible minority and immigrant status and period of immigration: Canada, provinces and territories, census metropolitan areas and census agglomerations with parts","year":2022,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Urban agglomeration; Immigration; Population; American Community Survey","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":[0.000171901,0.000377552,0.0004728461,0.0001300639,0.0005443085,0.0003072366,0.0001958417,0.00008537885,0.00002757919],"category_scores_gemma":[0.0000531794,0.000364014,0.00000876997,0.0002855604,0.0001714761,0.0001843709,0.0001827317,0.0002419079,1.418776e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005494756,"about_ca_system_score_gemma":0.001700676,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9531149,"about_ca_topic_score_gemma":0.9949619,"domain_scores_codex":[0.9975574,0.0001054385,0.0005050035,0.0006507189,0.0007812473,0.0004001783],"domain_scores_gemma":[0.9981782,0.0003400706,0.0003639036,0.0003703541,0.0002688775,0.0004786339],"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":[0.00003236484,0.000028921,0.001253778,0.0002790406,0.0000519939,0.0001112055,0.0002018152,0.000003485094,0.0000038294,0.002547601,0.9874126,0.008073356],"study_design_scores_gemma":[0.001033738,0.00102331,0.03038801,0.0002765818,0.0004399811,0.0002229148,0.004013749,0.01867346,0.00003725015,0.0002881806,0.9418519,0.001750913],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001799551,0.001360915,0.01158282,0.0004383292,0.0003392261,0.0005879572,0.9838689,0.00001098904,0.00001130674],"genre_scores_gemma":[0.09824193,0.000590928,0.003089451,0.00009745466,0.00006297084,0.0001086068,0.8976514,0.00001878139,0.0001384317],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09644238,"threshold_uncertainty_score":0.9998812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004956331559349084,"score_gpt":0.2241450631692831,"score_spread":0.219188731609934,"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."}}