{"id":"W3026649843","doi":"10.1111/cag.12623","title":"Canadian smart cities: Are we wiring new citizen‐local government interactions?","year":2020,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Smart city; CONTEST; Government (linguistics); Sustainability; Public relations; Business; Civic engagement; Transactional leadership; Local government; Political science; Public administration; Internet privacy; Politics; Internet of Things","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007827384,0.0007037646,0.0005951524,0.002188848,0.0006733907,0.0002846646,0.0008075006,0.0002961112,0.0004962852],"category_scores_gemma":[0.00008277845,0.0008230231,0.0003792572,0.00376641,0.0007122661,0.0004027703,0.00007115136,0.0006531877,0.00004551257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001135,"about_ca_system_score_gemma":0.0003979575,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9289227,"about_ca_topic_score_gemma":0.999539,"domain_scores_codex":[0.9964278,0.00002622075,0.0005332627,0.0006356539,0.0003568352,0.002020184],"domain_scores_gemma":[0.9952815,0.00009646126,0.00008657481,0.0005997393,0.00008777555,0.003847923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002492546,0.000009064588,0.177521,0.0003297042,0.0009780736,0.0008396454,0.003709377,0.002674175,0.00004510289,0.008077983,0.7666602,0.03913068],"study_design_scores_gemma":[0.000419127,0.00008675367,0.01973243,0.0002007501,0.00008580329,0.00007233434,0.05232082,0.001231432,0.000145613,0.00108648,0.9233142,0.001304215],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8820075,0.0138745,0.0003146205,0.0585146,0.004407875,0.001110995,0.001894649,0.003133457,0.03474184],"genre_scores_gemma":[0.9921846,0.004023171,0.0001709972,0.002541855,0.0003906044,0.00009355189,0.00005686653,0.0001483341,0.0003900627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1577886,"threshold_uncertainty_score":0.9994221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129399489628158,"score_gpt":0.1750407869951503,"score_spread":0.1637467920988687,"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."}}