{"id":"W4412692904","doi":"10.1007/s44196-025-00888-3","title":"Improved Crime Prediction Using Hybrid Neural Architecture Search Together with Hyperparameter Tuning","year":2025,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence Systems","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperparameter; Computer science; Hyperparameter optimization; Artificial intelligence; Machine learning; Artificial neural network; Pattern recognition (psychology); Data mining; Support vector machine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004282676,0.000159912,0.0002071331,0.0005796019,0.0001276121,0.0003853879,0.001065771,0.0000522667,0.000009384986],"category_scores_gemma":[0.00003460496,0.0001298516,0.0001221134,0.0003844983,0.00007017661,0.0005175325,0.0001252038,0.0003432586,0.000003359791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001979432,"about_ca_system_score_gemma":0.0002724002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006493037,"about_ca_topic_score_gemma":7.794456e-7,"domain_scores_codex":[0.9981191,0.0001085973,0.0006890656,0.000252547,0.0006594425,0.0001712978],"domain_scores_gemma":[0.9974829,0.0002209229,0.000379402,0.0001897558,0.001650158,0.00007689093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008195524,0.00009281281,0.0004202449,0.00001644171,0.0002506719,0.00002887442,0.0002246068,0.9317752,0.002679733,0.03360924,0.0001394099,0.03068079],"study_design_scores_gemma":[0.0001395643,0.0001634066,0.0002790969,0.00017052,0.00001589436,0.001212424,0.0001152068,0.9839575,0.005945154,0.007039359,0.0008402429,0.0001216678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03274385,0.0001525698,0.9648326,0.0006250312,0.0009832846,0.0002093065,0.00001228334,0.00007019522,0.0003708515],"genre_scores_gemma":[0.9101664,0.000006722525,0.08926831,0.0001881059,0.0002150367,0.00001057375,0.000004434666,0.000009868969,0.0001305236],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8774226,"threshold_uncertainty_score":0.5295194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02519490559520621,"score_gpt":0.3116027483846547,"score_spread":0.2864078427894485,"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."}}