{"id":"W7127359208","doi":"10.1109/sta66620.2025.11364711","title":"Hybrid Quantum–Classical Models for Forecasting and Anomaly Detection on Edge IoT Devices","year":2025,"lang":"","type":"article","venue":"","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Anomaly detection; Autoencoder; Enhanced Data Rates for GSM Evolution; Normalization (sociology); SPARK (programming language); Artificial neural network; Intrusion detection system; Preprocessor; Deep learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004767165,0.0004238189,0.0004758647,0.0002873183,0.000348693,0.0008495864,0.0009179329,0.0005555154,0.001988963],"category_scores_gemma":[0.001717886,0.0002354212,0.000343558,0.0003791924,0.0006424935,0.00181935,0.0006615968,0.001081577,0.0003273576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007741816,"about_ca_system_score_gemma":0.0005615405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005678708,"about_ca_topic_score_gemma":0.006175959,"domain_scores_codex":[0.9998148,0.00004419404,0.000007237399,0.00005105915,0.00005176439,0.00003093987],"domain_scores_gemma":[0.9995959,0.0002152028,0.00003766307,0.00005766274,0.00007133692,0.00002221713],"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":[0.0001036425,0.00006191977,0.001717561,0.00004724208,0.00003164568,0.00006538865,0.00005450473,0.9341686,0.004193797,0.02323077,0.001401065,0.0349239],"study_design_scores_gemma":[9.171447e-7,0.00000332231,0.0000470188,7.819531e-7,0.000001009699,0.000002269169,0.00000165987,0.9972696,0.0002545735,0.002319427,0.00009793141,0.00000142457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1075056,0.0003392788,0.8854139,0.0006022295,0.00007827025,0.00002980014,0.0002059324,0.0009792645,0.004845751],"genre_scores_gemma":[0.9236941,0.0002342862,0.07307949,0.0001716977,0.00003754451,0.00004322789,0.0002214113,0.00009159743,0.0024268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005678708,"threshold_uncertainty_score":0.01129133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02838597392586861,"score_gpt":0.2544720257252139,"score_spread":0.2260860517993453,"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."}}