{"id":"W3164747913","doi":"","title":"It Takes Three: Making Space for Cities in Canadian Federalism","year":2020,"lang":"en","type":"other","venue":"TSpace (University of Toronto)","topic":"Political Systems and Governance","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Federalism; Space (punctuation); Political science; Geography; Computer science; Politics; Law","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":[0.00120651,0.0004002753,0.0003301968,0.001235364,0.03426044,0.01169989,0.001606929,0.002261444,0.03854357],"category_scores_gemma":[0.003482549,0.0002563161,0.0005051902,0.003269629,0.0109635,0.003838979,0.005119586,0.003049387,0.001490963],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1367704,"about_ca_system_score_gemma":0.1444054,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9919076,"about_ca_topic_score_gemma":0.9977227,"domain_scores_codex":[0.9975513,0.0003638337,0.00002155768,0.0001759198,0.0004680882,0.001419452],"domain_scores_gemma":[0.9981977,0.0001391507,0.00006030046,0.0001022727,0.0005208002,0.0009797429],"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":[0.00009836971,0.00002825282,0.005770236,0.0001019575,0.00001861594,0.0002528644,0.0313504,0.001108475,0.0002573736,0.6675577,0.2381808,0.05527504],"study_design_scores_gemma":[0.00002016989,0.00001769562,0.0147475,0.0001853655,0.00002852271,0.0000631503,0.06532598,0.0006443775,0.000244758,0.03269905,0.8859454,0.00007796757],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.09288895,0.004109713,0.001955239,0.120881,0.0008111853,0.00006601203,0.0015376,0.0001777247,0.7775725],"genre_scores_gemma":[0.8826456,0.001612239,0.001233158,0.003507399,0.00007648194,0.00003494,0.0003440636,0.0001134258,0.1104327],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8632296,"threshold_uncertainty_score":0.9923437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02950603888284507,"score_gpt":0.2755143276850084,"score_spread":0.2460082888021633,"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."}}