{"id":"W4389666329","doi":"10.1109/nssmicrtsd49126.2023.10338406","title":"A Versatile Edge Machine Learning Test Bench for High Bandwidth Instrumentation","year":2023,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Canada Foundation for Innovation","keywords":"Test bench; Debugging; Computer science; Field-programmable gate array; Modular design; Instrumentation (computer programming); Data acquisition; Computer hardware; Embedded system; Automatic test equipment; Data compression; Enhanced Data Rates for GSM Evolution; Test data; Artificial intelligence; Engineering; Operating system; Reliability engineering","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":[0.0009752357,0.0006426724,0.0004653904,0.0009804434,0.0004934408,0.0007811219,0.001952042,0.0009571704,0.01049354],"category_scores_gemma":[0.002611343,0.0002722875,0.0002458507,0.0005548973,0.0004175275,0.0009388734,0.0007016693,0.0008454645,0.002129722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004566956,"about_ca_system_score_gemma":0.0005222223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004274985,"about_ca_topic_score_gemma":0.000384986,"domain_scores_codex":[0.9990044,0.0001481067,0.00006848131,0.0001610174,0.0004893448,0.0001286137],"domain_scores_gemma":[0.9975188,0.0008547308,0.0002182853,0.0004360432,0.000803347,0.0001688149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00175574,0.001092129,0.007922302,0.0009109479,0.0001164938,0.001731996,0.0003636649,0.02007556,0.7159472,0.008676184,0.01844448,0.2229633],"study_design_scores_gemma":[0.0001778632,0.00345631,0.01021163,0.00009499415,0.00005331373,0.001537443,0.00009650242,0.09633406,0.84501,0.001621183,0.04129039,0.0001162964],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2724383,0.0005838242,0.6907093,0.0004892084,0.0005320329,0.001132631,0.001791005,0.02138843,0.01093518],"genre_scores_gemma":[0.7600902,0.0002544447,0.2233815,0.0007784963,0.0001110282,0.001112669,0.001676885,0.001161701,0.01143306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01049354,"threshold_uncertainty_score":0.03510439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776339413378175,"score_gpt":0.2545166801678254,"score_spread":0.2367532860340436,"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."}}