{"id":"W2773860690","doi":"10.1080/17508975.2017.1394810","title":"Intelligent or smart cities and buildings: a critical exposition and a way forward","year":2017,"lang":"en","type":"article","venue":"Intelligent Buildings International","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Context (archaeology); Building automation; Exposition (narrative); Architectural engineering; Field (mathematics); Preference; Corporate governance; Smart city; Facility management; Computer science; Engineering; Knowledge management; Business; Computer security; Internet of Things; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0001684091,0.0002597947,0.0002296269,0.0002285132,0.0003122825,0.0006689518,0.0004764639,0.0001546861,0.0002791456],"category_scores_gemma":[0.0005829575,0.0002327463,0.0000706198,0.00003727807,0.000502824,0.0004909001,0.0003814642,0.0002488914,0.00001757446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001141597,"about_ca_system_score_gemma":0.00001073476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005307788,"about_ca_topic_score_gemma":0.00003037369,"domain_scores_codex":[0.9987306,0.000007424972,0.0003418761,0.0003298673,0.0002703369,0.0003198784],"domain_scores_gemma":[0.999231,0.0001899668,0.00006809375,0.0002869541,0.0001175027,0.0001064354],"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":[0.0003960029,0.0001691819,0.03944716,0.0005305714,0.0009563444,0.0002069961,0.003286891,0.0003541426,0.009152024,0.4908189,0.01957017,0.4351116],"study_design_scores_gemma":[0.001409372,0.0008443387,0.01515466,0.001749302,0.0002113263,0.001276701,0.006713212,0.06286526,0.337361,0.1088581,0.4610786,0.002478136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208149,0.0009934322,0.06585076,0.002734512,0.002375796,0.0002303879,0.00005034458,0.0005905202,0.006359362],"genre_scores_gemma":[0.9916951,0.002468808,0.004959725,0.0001248682,0.0002404134,0.0000607211,0.000007289371,0.00003834994,0.0004047219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4415084,"threshold_uncertainty_score":0.9491119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02529425490316494,"score_gpt":0.2808295791514914,"score_spread":0.2555353242483264,"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."}}