{"id":"W6888925006","doi":"10.25318/9810023901-eng","title":"Structural type of dwelling by tenure: Canada, provinces and territories, census metropolitan areas and census agglomerations","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":[0.0007992339,0.002056724,0.001870711,0.00593589,0.001965008,0.002870622,0.004221976,0.001300853,0.05950202],"category_scores_gemma":[0.00729003,0.001342045,0.001748779,0.02330054,0.0004945354,0.001544062,0.001772417,0.00238201,0.01894579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01733471,"about_ca_system_score_gemma":0.0374553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9785513,"about_ca_topic_score_gemma":0.9842926,"domain_scores_codex":[0.9985428,0.00006344847,0.0001569291,0.0002443574,0.0004949019,0.0004976285],"domain_scores_gemma":[0.9930101,0.0003282195,0.0005320679,0.0002981203,0.005172218,0.0006592745],"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":[0.00003543177,0.00001342551,0.004013105,0.0004172537,0.00003513255,0.00001265254,0.00004327431,0.0001934593,0.00001400256,0.0004697046,0.993004,0.001748469],"study_design_scores_gemma":[0.0004577382,0.00002519211,0.1542853,0.001609624,0.0001403736,0.00008787245,0.0008869819,0.0009338798,0.0002423276,0.0009402036,0.8402957,0.00009486212],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001644318,0.00004890701,0.00002200005,0.00003965784,0.00001223074,0.00001387732,0.9991314,0.00002323385,0.0005442524],"genre_scores_gemma":[0.002231765,0.0002037455,0.0002502478,0.00007092396,0.0000100344,0.000145622,0.9942937,0.00003818974,0.002755794],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05950202,"threshold_uncertainty_score":0.1990541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00863494444281926,"score_gpt":0.2621388373745688,"score_spread":0.2535038929317496,"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."}}