{"id":"W2116947468","doi":"10.1109/delta.2008.77","title":"Improving Cost-Effectiveness Using a Micro-level Static Architecture for Stream Applications","year":2008,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Control reconfiguration; Redundancy (engineering); Field-programmable gate array; Embedded system; Frame rate; Architecture; Real-time computing; Computer architecture; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003478848,0.000167015,0.000209479,0.0001477076,0.0002599848,0.00007212127,0.0006472094,0.00007249975,0.000001610367],"category_scores_gemma":[0.00003674281,0.0001493644,0.00008096808,0.0003204805,0.00004999499,0.0002345705,0.0001267172,0.0001034339,0.000005070219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001372211,"about_ca_system_score_gemma":0.0001714239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001844233,"about_ca_topic_score_gemma":0.00001601589,"domain_scores_codex":[0.9987466,0.0001126218,0.0002393861,0.0004414557,0.0001566027,0.0003033188],"domain_scores_gemma":[0.9985898,0.0004342967,0.0001207918,0.0006184588,0.0001574014,0.00007928633],"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":[0.00002261207,0.0002371616,0.0006565184,0.0006104612,0.00006642101,0.00001490566,0.001460917,0.00110042,0.7691165,0.03449425,0.0006481133,0.1915718],"study_design_scores_gemma":[0.001202625,0.0003059013,0.0007663392,0.0001522096,0.00002942352,0.0006469269,0.00007789082,0.2448352,0.7261323,0.02142248,0.003477748,0.0009509352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007436853,0.00004179102,0.9884512,0.00003908232,0.00004641809,0.003238165,0.00001989658,0.0005322229,0.000194345],"genre_scores_gemma":[0.2851939,0.000001129719,0.7133643,0.00008442083,0.00003783704,0.001208204,0.00000351754,0.0000172716,0.00008934246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2777571,"threshold_uncertainty_score":0.6090902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08688100200857944,"score_gpt":0.3243145313124809,"score_spread":0.2374335293039015,"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."}}