{"id":"W4408347280","doi":"10.1109/icassp49660.2025.10889685","title":"Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks","year":2025,"lang":"en","type":"article","venue":"","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multivariate statistics; Computer science; Artificial intelligence; Graph; Artificial neural network; Machine learning; Pattern recognition (psychology); Data mining; Theoretical 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002108456,0.00009881307,0.0001124954,0.00008955863,0.0005034687,0.0001248552,0.0001494614,0.00007708493,0.001499313],"category_scores_gemma":[0.00001533481,0.00007752421,0.000100674,0.0002981578,0.00014543,0.0001834949,0.00003663148,0.0001385761,0.000006812616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005669054,"about_ca_system_score_gemma":0.0000571188,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1260509,"about_ca_topic_score_gemma":0.05208613,"domain_scores_codex":[0.999045,0.0001261706,0.0001867258,0.0002150353,0.0001725648,0.0002544804],"domain_scores_gemma":[0.9995967,0.00004094106,0.00005047767,0.0001296194,0.0001122761,0.00007005049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004375283,0.000832833,0.745243,0.00006050648,0.0004063566,0.00002345883,0.00552065,0.02351885,0.00007146088,0.051281,0.09200103,0.08060335],"study_design_scores_gemma":[0.002975091,0.0006871893,0.4048769,0.0003493188,0.000247414,0.000002436426,0.01303915,0.495932,0.00008973561,0.002213774,0.07887872,0.0007083016],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1175323,0.00008294667,0.7627783,0.003764669,0.002024791,0.000785419,0.00004698604,0.0005517455,0.1124328],"genre_scores_gemma":[0.9904172,0.000005407398,0.0001042221,0.0002311392,0.0002209948,0.00002494021,0.0000342572,0.000006118795,0.008955665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8728849,"threshold_uncertainty_score":0.9994134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428797903908231,"score_gpt":0.3289143186698497,"score_spread":0.3046263396307674,"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."}}