{"id":"W4414090500","doi":"10.4018/979-8-3373-2125-7.ch004","title":"Edge Intelligence Expanding BI Architectures Beyond the Cloud","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Cloud computing; Orchestration; Container (type theory); Analytics; Process (computing); Enhanced Data Rates for GSM Evolution; Business intelligence; Edge device; Edge computing","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":[0.0004586742,0.000541749,0.0002870305,0.0007384468,0.0008246322,0.005687301,0.001157652,0.0009295997,0.006941231],"category_scores_gemma":[0.0006196585,0.0004545808,0.0005463975,0.001851443,0.0007648435,0.007459775,0.002609836,0.002557285,0.003926378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364671,"about_ca_system_score_gemma":0.001064696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00266484,"about_ca_topic_score_gemma":0.00313545,"domain_scores_codex":[0.9996033,0.00004957161,0.00001701338,0.00006871725,0.0001820597,0.00007933806],"domain_scores_gemma":[0.9997416,0.00005891514,0.00001020762,0.00006912206,0.00008459825,0.00003552887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003969035,0.00004051975,0.0002294068,0.0002125006,0.00001630271,0.0001250326,0.0004015022,0.007464734,0.003429374,0.7466725,0.05042917,0.1909393],"study_design_scores_gemma":[0.0000071558,0.00002129909,0.0002122938,0.0002046399,0.00001305919,0.0002409273,0.0002066288,0.03315761,0.00310731,0.178369,0.7844393,0.00002074638],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01717858,0.02906715,0.3579635,0.008168525,0.001853667,0.0001962479,0.0004226843,0.002972768,0.5821768],"genre_scores_gemma":[0.2566882,0.06773834,0.3893024,0.003960144,0.001271816,0.0002398728,0.002089952,0.001526967,0.2771823],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.006941231,"threshold_uncertainty_score":0.02322072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0215569988818253,"score_gpt":0.2559945438720525,"score_spread":0.2344375449902272,"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."}}