{"id":"W2899995290","doi":"10.11575/sppp.v11i0.58368","title":"Social Policy Trends: Monthly Rent Payments in the Twenty Largest Canadian Census Metropolitan Areas (2017)","year":2018,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic rent; Census; Metropolitan area; Payment; Distribution (mathematics); Geography; Economics; Point (geometry); Demographic economics; Demography; Finance; Population; Market economy","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":[0.0006548626,0.0005698954,0.0004473833,0.006356101,0.003522677,0.00274248,0.001639473,0.0006500091,0.008962987],"category_scores_gemma":[0.004308158,0.0003376694,0.000747652,0.01499473,0.0007174754,0.001095057,0.001339402,0.001283624,0.001402633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06138768,"about_ca_system_score_gemma":0.08860858,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9985436,"about_ca_topic_score_gemma":0.9992616,"domain_scores_codex":[0.9982968,0.00005930221,0.0001026344,0.0001205412,0.0008159706,0.0006047256],"domain_scores_gemma":[0.9941526,0.0001506918,0.0005577091,0.00007022112,0.004159266,0.0009094428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001813733,0.00009443612,0.5038751,0.0005010437,0.0001332128,0.0001404845,0.00222865,0.0008825441,0.000202162,0.005493918,0.4384886,0.04777841],"study_design_scores_gemma":[0.00001583622,0.00001390732,0.917531,0.0001740668,0.00003178386,0.00004930095,0.003431022,0.0008182107,0.0001232577,0.0002356674,0.07753515,0.00004081849],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3619431,0.007283411,0.0004242564,0.01728451,0.0005269598,0.0001932588,0.5549913,0.0003937314,0.05695944],"genre_scores_gemma":[0.7568374,0.009358331,0.001229755,0.001898811,0.0002320649,0.0002203447,0.1924126,0.0001507896,0.03765991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06138768,"threshold_uncertainty_score":0.4454009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2357052526299004,"score_gpt":0.5511395415579402,"score_spread":0.3154342889280398,"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."}}