{"id":"W7113638779","doi":"","title":"Metropolitan Housing Futures: Urban Planning Timescapes in Greater Boston and Greater Montréal","year":2025,"lang":"","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Urban planning; Urban poverty; Regional planning; Urban density","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":[0.0007170895,0.0003055988,0.0001727141,0.001391302,0.01027393,0.005450368,0.0008330346,0.0007848499,0.06238628],"category_scores_gemma":[0.001734892,0.0003210075,0.0001756799,0.004958858,0.002180137,0.001955641,0.002402449,0.0009288441,0.00147018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05998289,"about_ca_system_score_gemma":0.03583935,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9818228,"about_ca_topic_score_gemma":0.996906,"domain_scores_codex":[0.9993758,0.0001210398,0.000008082279,0.00004859354,0.0001340884,0.0003123947],"domain_scores_gemma":[0.9985015,0.00009131098,0.00008986396,0.00002210105,0.0002347446,0.001060475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001744682,0.00009533422,0.06257077,0.0002078472,0.00003163835,0.0007360408,0.08836719,0.0008811884,0.0006690629,0.07812119,0.6598567,0.1082885],"study_design_scores_gemma":[0.00001090172,0.00002403215,0.1864437,0.0001350615,0.000008561552,0.00007211478,0.1412276,0.0003280177,0.0001451856,0.001618896,0.6699369,0.00004901647],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4672676,0.02643292,0.0007420594,0.1255681,0.001357107,0.000115514,0.01073901,0.000308754,0.367469],"genre_scores_gemma":[0.6866414,0.005433108,0.0005196515,0.001070057,0.0001526295,0.0000548803,0.001191235,0.0001305974,0.3048064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06238628,"threshold_uncertainty_score":0.4352084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131722020698945,"score_gpt":0.2386288885852812,"score_spread":0.2254566865153867,"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."}}