{"id":"W3140180964","doi":"10.48550/arxiv.2104.03818","title":"A Network-based Compute Reuse Architecture for IoT Applications","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Architecture; Computer science; Reuse; Internet of Things; Computer architecture; Distributed computing; Computer network; Software engineering; Embedded system; Engineering; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002787411,0.0003642913,0.0004097427,0.000197027,0.0004139571,0.0003577908,0.003333854,0.0003149693,0.000002359539],"category_scores_gemma":[0.00003148823,0.0004434798,0.0003695959,0.0008644946,0.00007808187,0.0001034249,0.003286991,0.0006610659,0.00001598008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001558669,"about_ca_system_score_gemma":0.0006055371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003547876,"about_ca_topic_score_gemma":0.00001597121,"domain_scores_codex":[0.9975747,0.0001270644,0.0002415292,0.001389007,0.00009152245,0.0005761783],"domain_scores_gemma":[0.9964841,0.0003520724,0.0002733296,0.002415326,0.0002840242,0.0001911203],"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":[0.00001634501,0.00009167341,0.0002828231,0.0001552002,0.00007428919,0.0000734561,0.0001773764,0.969249,0.00001037403,0.01848243,0.006033378,0.005353719],"study_design_scores_gemma":[0.0005047967,0.00003979458,0.0001974172,0.0001507193,0.00006519205,0.000004493972,0.000007762504,0.9116093,0.00004284974,0.05745894,0.02938006,0.0005387135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01238871,0.0001507015,0.981987,0.0006286222,0.003240927,0.0007822084,0.000003018312,0.0004482773,0.0003705278],"genre_scores_gemma":[0.5976015,0.00002246036,0.3958324,0.001292563,0.004403454,0.0000225502,0.0001659076,0.00006359872,0.0005954618],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5861545,"threshold_uncertainty_score":0.9998017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06778921901155423,"score_gpt":0.1884533941521797,"score_spread":0.1206641751406254,"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."}}