{"id":"W4390483843","doi":"10.1109/ssci52147.2023.10371940","title":"Advancing Smart Cities Through Novel Social Media Text Analysis: A Case Study of Calgary","year":2023,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Social media; Data science; Computer science; Variety (cybernetics); Smart city; Set (abstract data type); Urban planning; Bureaucracy; Sentiment analysis; Population; Perception; Artificial intelligence; World Wide Web; Political science; Sociology; Politics; Engineering; Psychology; Internet of Things","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":[0.001092838,0.0005814005,0.0003010167,0.00162259,0.005888701,0.002482233,0.001341702,0.001904862,0.001495351],"category_scores_gemma":[0.003143526,0.0002144894,0.0002568705,0.003308368,0.002478894,0.001456498,0.001690859,0.001370442,0.0003925207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004882717,"about_ca_system_score_gemma":0.00234317,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2228877,"about_ca_topic_score_gemma":0.4556103,"domain_scores_codex":[0.999008,0.0004421984,0.00003821072,0.0001538271,0.0001694959,0.0001882806],"domain_scores_gemma":[0.9978957,0.00119749,0.0001726051,0.0001321745,0.0003198477,0.0002821309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004268987,0.001958369,0.1568075,0.000673465,0.0002170206,0.0629613,0.564638,0.009812606,0.01126782,0.008594885,0.03046393,0.1521783],"study_design_scores_gemma":[0.00006800742,0.0002664925,0.158722,0.0001595145,0.00007284812,0.001681383,0.741728,0.02117166,0.003809018,0.002360915,0.06985934,0.0001008384],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923508,0.0001030249,0.001220793,0.001430397,0.00002249699,0.000134023,0.0003891671,0.00005774226,0.004291699],"genre_scores_gemma":[0.9848745,0.0003957663,0.006011787,0.0007134831,0.00005267562,0.00012063,0.0006554861,0.00009559321,0.00707995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7771122,"threshold_uncertainty_score":0.4431807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04882676916612464,"score_gpt":0.3442873849231619,"score_spread":0.2954606157570372,"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."}}