{"id":"W4388974454","doi":"10.1080/13658816.2023.2279978","title":"GeoAI in urban analytics","year":2023,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Analytics; Geography; Data science; Computer science","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":[0.004208391,0.0001232701,0.0002974506,0.003248259,0.0001794067,0.0004082729,0.0006825238,0.0001697867,0.00002887116],"category_scores_gemma":[0.0007572875,0.0001115882,0.0002167181,0.002193292,0.0001881718,0.002632747,0.00007431884,0.0003124248,0.0002285187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001447952,"about_ca_system_score_gemma":0.0001508282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00108916,"about_ca_topic_score_gemma":0.0001676472,"domain_scores_codex":[0.9957846,0.0001651041,0.001699001,0.00006656326,0.001962269,0.0003224979],"domain_scores_gemma":[0.9962256,0.0002740725,0.001011938,0.0001149719,0.002227962,0.0001454574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001205475,0.0000821244,0.6023922,0.0000695821,0.0005541759,0.00006034019,0.06378631,0.00838317,0.000005720164,0.2903717,0.02953654,0.004637591],"study_design_scores_gemma":[0.001227128,0.00005990003,0.1066636,0.000243393,0.0000156124,0.00004915979,0.05198636,0.002073969,0.000002179529,0.0008728593,0.836574,0.0002319119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.777889,0.0006264479,0.004909388,0.01593517,0.02808498,0.001460407,0.0001244248,0.0005185054,0.1704516],"genre_scores_gemma":[0.9984986,0.0004833524,0.00003738461,0.0002077711,0.0005302145,0.00001325033,0.00001994277,0.000004926754,0.0002045731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8070374,"threshold_uncertainty_score":0.4550435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457854890520193,"score_gpt":0.3170407978607015,"score_spread":0.2924622489554995,"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."}}