{"id":"W3124795730","doi":"","title":"The Context and Challenges for Canada's Mid-Sized Cities","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Business; Payroll; Context (archaeology); Population; Government (linguistics); Economics; Economic policy; Public economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.002597174,0.0006272724,0.0006917492,0.001968679,0.04131545,0.0153805,0.004509668,0.00346772,0.01018042],"category_scores_gemma":[0.005077705,0.0006310879,0.0009544815,0.004257182,0.008433336,0.00269404,0.007035497,0.006899286,0.0006031423],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2513581,"about_ca_system_score_gemma":0.4261306,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9986976,"about_ca_topic_score_gemma":0.9994916,"domain_scores_codex":[0.9933854,0.0004519303,0.0001495366,0.0004512998,0.001358845,0.00420293],"domain_scores_gemma":[0.9874448,0.0005986976,0.0003836694,0.0002054176,0.003372773,0.007994641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002780631,0.0002144865,0.06249757,0.0008245992,0.0001433082,0.005348195,0.0475321,0.002796947,0.001342726,0.4102218,0.3833313,0.08546897],"study_design_scores_gemma":[0.00005937724,0.00005726138,0.1044762,0.0008939007,0.00009220615,0.000846185,0.1208349,0.001921803,0.0003066199,0.02009055,0.7501336,0.0002873355],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2605953,0.01501402,0.002050446,0.4977995,0.002026515,0.0003406635,0.004909378,0.0002971505,0.2169671],"genre_scores_gemma":[0.887772,0.006697235,0.003362328,0.04577257,0.0002426905,0.0001321145,0.001172375,0.0001261712,0.05472244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7486419,"threshold_uncertainty_score":0.8683185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157445458495638,"score_gpt":0.2740441655954455,"score_spread":0.2524697110104891,"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."}}