{"id":"W3138369140","doi":"10.5772/intechopen.96618","title":"Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing","year":2021,"lang":"en","type":"book-chapter","venue":"IntechOpen eBooks","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Blockchain; Scalability; Server; Edge computing; Artificial intelligence; Data sharing; Enhanced Data Rates for GSM Evolution; Mobile edge computing; Big data; Computer security; Data science; Distributed computing; World Wide Web; Database; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001136241,0.0004066029,0.0005483593,0.0006100865,0.0007641817,0.002340186,0.0007967501,0.001270161,0.007173369],"category_scores_gemma":[0.002126539,0.0002305971,0.0003270725,0.00147863,0.001529606,0.004671712,0.002139836,0.001444871,0.001614938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150595,"about_ca_system_score_gemma":0.001372141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007716362,"about_ca_topic_score_gemma":0.0009251869,"domain_scores_codex":[0.9990938,0.0003069013,0.00004460177,0.0001171256,0.0003090215,0.0001286059],"domain_scores_gemma":[0.9992287,0.000380361,0.00005793314,0.0001753769,0.0001000909,0.0000575552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000886608,0.00004616334,0.0003040296,0.0004118938,0.00001939626,0.0002849554,0.0002695365,0.02427714,0.003123473,0.8662053,0.006946536,0.09802281],"study_design_scores_gemma":[0.000034105,0.00007105301,0.0002235907,0.0003046544,0.00001316725,0.0003566826,0.000121634,0.1024512,0.004332615,0.7526269,0.1394349,0.00002939974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04858861,0.03852835,0.7543249,0.008861667,0.0008414582,0.000402568,0.0006433347,0.001175725,0.1466335],"genre_scores_gemma":[0.7946649,0.04484254,0.1075209,0.001086416,0.0006893952,0.0005963425,0.0009309059,0.0001814698,0.04948723],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007173369,"threshold_uncertainty_score":0.02399731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329031139722008,"score_gpt":0.2795358739408826,"score_spread":0.2462455625436625,"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."}}