{"id":"W2911304175","doi":"10.17269/s41997-019-00177-5","title":"Towards ‘smart cities’ as ‘healthy cities’: health equity in a digital age","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Cumming School of Medicine, University of Calgary; Calgary Institute for the Humanities, University of Calgary; O'Brien Institute for Public Health, University of Calgary; University of Calgary","keywords":"Conceptualization; Equity (law); Mental health; Smart city; Promotion (chess); Health promotion; Health equity; Economic growth; Political science; Sociology; Public relations; Internet of Things; Psychology; Internet privacy; Economics; Health care; Computer science; Politics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007588226,0.000206342,0.0007020307,0.001452474,0.000566767,0.0004664704,0.001048547,0.0002616639,0.0005062374],"category_scores_gemma":[0.002289955,0.0002198715,0.0001344449,0.001176838,0.0005599361,0.001083302,0.0000626632,0.001043191,0.0001060888],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007479238,"about_ca_system_score_gemma":0.1190788,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.398958,"about_ca_topic_score_gemma":0.8303023,"domain_scores_codex":[0.9949414,0.0005148603,0.001126373,0.0003021052,0.0007594756,0.002355793],"domain_scores_gemma":[0.9938461,0.0001387261,0.0007254497,0.0003439409,0.0003212706,0.004624572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002112048,0.0001086062,0.2702637,0.0002359421,0.00005259491,0.0003905046,0.1042282,0.00000288498,4.114431e-7,0.2090947,0.04339876,0.3722026],"study_design_scores_gemma":[0.001346517,0.001207431,0.08804915,0.0002984519,0.000001721121,0.0001302307,0.05343994,0.000004760363,3.852613e-7,0.01363261,0.841579,0.0003098621],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6789317,0.001428856,0.00009929231,0.2652923,0.001736437,0.0006222639,0.00008843601,0.00006249699,0.0517382],"genre_scores_gemma":[0.9845874,0.0003198989,0.0002044463,0.01332087,0.0002695475,0.000005138124,0.00001017852,0.0000280612,0.0012545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7981802,"threshold_uncertainty_score":0.9963309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06691872978822659,"score_gpt":0.3580952127618104,"score_spread":0.2911764829735838,"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."}}