{"id":"W4407914267","doi":"10.1007/978-3-031-84356-3_9","title":"On Handling AI Tasks in CPU with Low Latency and High Performance","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Latency (audio); Operating system; Embedded system; Parallel computing; Telecommunications","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":[0.0005975848,0.0009126159,0.0005819882,0.0007185398,0.001026817,0.00171388,0.002275231,0.0005953727,0.008980165],"category_scores_gemma":[0.002849572,0.0003567342,0.0004371546,0.001705555,0.0005531932,0.002658273,0.001648517,0.00146892,0.002664657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005890872,"about_ca_system_score_gemma":0.00125508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004039923,"about_ca_topic_score_gemma":0.00483694,"domain_scores_codex":[0.9994074,0.00009432546,0.000054329,0.0000929072,0.0002000444,0.0001509578],"domain_scores_gemma":[0.9982544,0.000873471,0.00006514114,0.000361617,0.0003490535,0.00009645525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001421031,0.0002702621,0.002076824,0.0007222221,0.00008715763,0.0004104491,0.0005054541,0.05500802,0.04447272,0.04136835,0.05403932,0.7996182],"study_design_scores_gemma":[0.0001216138,0.0004825655,0.001924053,0.0001516195,0.0001303728,0.00061641,0.0003832414,0.8176624,0.03378826,0.08050486,0.06416354,0.00007105301],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06261823,0.008621576,0.8803886,0.001361835,0.001453576,0.0003097194,0.0004023056,0.006054441,0.03878976],"genre_scores_gemma":[0.3729174,0.004283561,0.5698984,0.001030855,0.0009768517,0.0003280889,0.001150211,0.001196694,0.04821802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008980165,"threshold_uncertainty_score":0.03004164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007400626216228475,"score_gpt":0.2264062445350989,"score_spread":0.2190056183188705,"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."}}