{"id":"W3209322995","doi":"10.1145/3479242.3487321","title":"Automated and Reproducible Application Traces Generation for IoT Applications","year":2021,"lang":"en","type":"preprint","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"CHIST-ERA; Agence Nationale de la Recherche","keywords":"Computer science; Testbed; TRACE (psycholinguistics); Focus (optics); Internet of Things; Software; Replication (statistics); Usability; Scale (ratio); Software engineering; Distributed computing; Embedded system; World Wide Web; Human–computer interaction; 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":[0.00310215,0.001534881,0.001094202,0.002884334,0.0009114623,0.002854407,0.002234057,0.001387382,0.002930593],"category_scores_gemma":[0.02221211,0.0007955676,0.0009035445,0.001985898,0.0008849757,0.002306677,0.00271703,0.001952065,0.002299838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007796573,"about_ca_system_score_gemma":0.003010401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00277426,"about_ca_topic_score_gemma":0.003525517,"domain_scores_codex":[0.993579,0.001386038,0.0004702131,0.001332233,0.002806479,0.0004259095],"domain_scores_gemma":[0.9758254,0.005919461,0.001326817,0.01138579,0.004992453,0.0005501267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001242712,0.0007717598,0.01712547,0.0006329085,0.0003023017,0.001191531,0.0007257764,0.09498403,0.1541857,0.01788954,0.02171857,0.6892297],"study_design_scores_gemma":[0.00008407314,0.0001720037,0.003970949,0.0000775788,0.00006739405,0.000503062,0.000221775,0.8250288,0.1248586,0.0322093,0.01274432,0.00006214116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04235918,0.0002307752,0.9313179,0.0003862053,0.0001740392,0.0004146724,0.001540493,0.02155696,0.002019654],"genre_scores_gemma":[0.5581544,0.0002419012,0.4303289,0.0001775024,0.0001292145,0.0003921491,0.004705358,0.002647674,0.003222943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00310215,"threshold_uncertainty_score":0.01640594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03937044197141514,"score_gpt":0.3011663749263245,"score_spread":0.2617959329549094,"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."}}