{"id":"W3010808776","doi":"10.17645/up.v5i1.2520","title":"Googling the City: In Search of the Public Interest on Toronto’s ‘Smart’ Waterfront","year":2020,"lang":"en","type":"article","venue":"Urban Planning","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Realm; Narrative; Smart city; General partnership; Scope (computer science); Corporate governance; Power (physics); Plan (archaeology); Urbanism; Political science; Public relations; Sociology; Public administration; Engineering; Business; Geography; Internet of Things; Computer science","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":[0.001686057,0.0003116582,0.0001971621,0.0007350168,0.03072034,0.01465025,0.001210802,0.003889323,0.01135254],"category_scores_gemma":[0.003163115,0.0003738298,0.000271546,0.001794644,0.03133569,0.005257442,0.005417108,0.004326271,0.0005738859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08001994,"about_ca_system_score_gemma":0.04525905,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7758877,"about_ca_topic_score_gemma":0.9219915,"domain_scores_codex":[0.998013,0.0007093467,0.00002000063,0.0001447551,0.0003764942,0.0007362883],"domain_scores_gemma":[0.9978678,0.0008797082,0.0001534551,0.0001337515,0.000292743,0.0006724943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004927971,0.00002050061,0.002616893,0.00009980384,0.000008130784,0.00173969,0.3382435,0.0008177793,0.0006338406,0.5809152,0.06036393,0.01449151],"study_design_scores_gemma":[0.00000929847,0.00001714594,0.002364401,0.0001203718,0.00001186738,0.0001632064,0.3611875,0.0005634818,0.0006381896,0.01724908,0.6176354,0.00004013716],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3322062,0.003825552,0.005360462,0.1665685,0.000708367,0.00008888374,0.0002333699,0.0001454102,0.4908632],"genre_scores_gemma":[0.9348884,0.0009824814,0.0004945558,0.003267183,0.00005521798,0.0000202367,0.00004208763,0.00008130649,0.0601686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2241123,"threshold_uncertainty_score":0.580588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06282773747618488,"score_gpt":0.2345994061910129,"score_spread":0.171771668714828,"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."}}