{"id":"W4381378213","doi":"10.21203/rs.3.rs-3069205/v1","title":"Intelligent Edge CDN with Smart Contract-Aided Local IoT Sharing","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Cache; Server; Content delivery network; Computer network; End user; Schedule; Smart contract; Content delivery; Database transaction; Database; Operating system","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":[0.001292904,0.0003878399,0.0006802599,0.0003589667,0.0009562729,0.001445888,0.001682866,0.0008934588,0.003666437],"category_scores_gemma":[0.002089155,0.000189132,0.0003153656,0.000539946,0.0008941563,0.00229163,0.002805448,0.0007817575,0.0005045685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376779,"about_ca_system_score_gemma":0.00108634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003441244,"about_ca_topic_score_gemma":0.00264651,"domain_scores_codex":[0.9990638,0.0002501975,0.00004889558,0.0002245618,0.0002125715,0.0001998911],"domain_scores_gemma":[0.9988286,0.0003867419,0.0001422606,0.0002549299,0.0002244504,0.0001630512],"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":[0.0006574863,0.0003299894,0.002424423,0.00006874215,0.00004234423,0.0004282302,0.0002169634,0.8656787,0.009521606,0.04516393,0.003640861,0.07182675],"study_design_scores_gemma":[0.00001605839,0.00002672683,0.00007931626,0.000002592466,0.000004609101,0.0000382896,0.00003363561,0.9917618,0.001116172,0.005957619,0.0009557496,0.000007508714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2484776,0.0003216738,0.7354552,0.0005753216,0.0001223351,0.0001640932,0.0001550381,0.001032685,0.01369609],"genre_scores_gemma":[0.9763595,0.00003741067,0.02148811,0.00008303356,0.00001105657,0.00002603914,0.00004251436,0.00002434535,0.001927915],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003666437,"threshold_uncertainty_score":0.01226544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486090027207287,"score_gpt":0.3776586628759356,"score_spread":0.2290496601552069,"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."}}