{"id":"W3158921294","doi":"10.24908/cpp-apc.v2021i01.14607","title":"Housing challenges, mid-sized cities and the COVID-19 pandemic","year":2021,"lang":"en","type":"article","venue":"Canadian Planning and Policy / Aménagement et politique au Canada","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Canada Research Chairs","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Critical reflection; 2019-20 coronavirus outbreak; Situated; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Geography; Inequality; Political science; Economic geography; Economic growth; Regional science; Development economics; Sociology; Economics; Medicine; Computer science; Virology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001330158,0.000255507,0.0003143277,0.0009775613,0.01333717,0.006058748,0.001154249,0.001497558,0.002463487],"category_scores_gemma":[0.002646831,0.000189449,0.0002734016,0.001774015,0.008850831,0.002881569,0.004441608,0.003332072,0.0001071583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05736409,"about_ca_system_score_gemma":0.05211566,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9496909,"about_ca_topic_score_gemma":0.9754887,"domain_scores_codex":[0.998379,0.0002716226,0.00003978486,0.00009477391,0.0002330043,0.0009818048],"domain_scores_gemma":[0.9982072,0.0001925074,0.0002185376,0.00004774691,0.0004714641,0.0008625331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001247004,0.0001185278,0.1616557,0.0005562019,0.00007098259,0.003392224,0.4658408,0.001874089,0.0008863179,0.2302697,0.0773452,0.05786562],"study_design_scores_gemma":[0.000006263603,0.00003511669,0.1422263,0.0006480731,0.00001645439,0.0003792566,0.6953119,0.0004229776,0.0002200974,0.009457553,0.1512045,0.00007150923],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7379242,0.01540306,0.0009308697,0.1696534,0.0009643578,0.0001035711,0.0010421,0.0000320485,0.07394645],"genre_scores_gemma":[0.990072,0.0043337,0.0002758082,0.003028031,0.00008415975,0.000026927,0.0001418276,0.000009685855,0.002027754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05736409,"threshold_uncertainty_score":0.4162076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07730828541410424,"score_gpt":0.3351463414378335,"score_spread":0.2578380560237293,"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."}}