{"id":"W2116002481","doi":"10.1109/ccece.2007.353","title":"Pipeline Design and Verification in Bluenose II","year":2007,"lang":"en","type":"article","venue":"","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Pipeline (software); Formal verification; Functional verification; Time to market; Abstraction; Pipeline transport; Intelligent verification; Model checking; High-level verification; Runtime verification; Formal methods; Software engineering; Verification; Embedded system; Reliability engineering; Programming language; Software; Engineering; Software development","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":[0.00115906,0.0004193696,0.000337014,0.0004630403,0.0003438372,0.001000887,0.0006909128,0.0004997039,0.006785959],"category_scores_gemma":[0.001688942,0.0005324639,0.0005480246,0.0003060408,0.001050344,0.001492226,0.0009509674,0.0008370461,0.001012511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000756154,"about_ca_system_score_gemma":0.001188044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002831213,"about_ca_topic_score_gemma":0.003506548,"domain_scores_codex":[0.9990531,0.0002674966,0.00004354885,0.0001321135,0.0004141488,0.00008961312],"domain_scores_gemma":[0.9993475,0.0002414,0.00005176675,0.0002051472,0.0001336854,0.00002048763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006671672,0.0001206975,0.001543463,0.0007598554,0.00005887867,0.0008131656,0.0009420732,0.1247951,0.08478007,0.4586981,0.01352727,0.3132941],"study_design_scores_gemma":[0.0002913394,0.0003884259,0.001054042,0.0002571879,0.0000514962,0.0006154533,0.000119406,0.4024452,0.08024388,0.2400358,0.274431,0.0000667885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02769819,0.0004717051,0.9407372,0.000510013,0.00009514558,0.000165447,0.0001690575,0.004125853,0.0260275],"genre_scores_gemma":[0.28353,0.0005559665,0.6803396,0.0004895385,0.00004846824,0.0002626406,0.0004433904,0.0008399881,0.03349042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006785959,"threshold_uncertainty_score":0.02270132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03727691401040105,"score_gpt":0.3072752483619198,"score_spread":0.2699983343515188,"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."}}