{"id":"W2128754884","doi":"10.1002/cpe.1065","title":"A methodology for early validation of cache coherence protocols based on relational databases","year":2006,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Correctness; Cache coherence; Protocol (science); Relational database; Table (database); Database; Cache; Relational algebra; Multiprocessing; Programming language; Theoretical computer science; Cache algorithms; CPU cache; Parallel computing","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":[0.01670027,0.0007802366,0.0009399112,0.001955596,0.001001974,0.004989014,0.004537645,0.001610292,0.002573615],"category_scores_gemma":[0.03379002,0.001349416,0.001875601,0.0008567761,0.003370826,0.005534204,0.003429511,0.002830198,0.0008186487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726799,"about_ca_system_score_gemma":0.003617897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002370877,"about_ca_topic_score_gemma":0.001419866,"domain_scores_codex":[0.9789969,0.00896518,0.0018675,0.002045645,0.007346843,0.0007779822],"domain_scores_gemma":[0.9667351,0.01606351,0.002217263,0.009066759,0.005553764,0.0003636349],"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":[0.0003177534,0.0002596761,0.002798587,0.0006765753,0.0002492581,0.001100295,0.001956821,0.09867311,0.04003146,0.6685079,0.002149668,0.1832789],"study_design_scores_gemma":[0.0001891524,0.0003285421,0.0005103659,0.0003002742,0.0002199218,0.0008065061,0.0002961477,0.6760983,0.1094198,0.173279,0.03839828,0.0001536529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003299871,0.00007534398,0.9948264,0.00007924225,0.00001572606,0.00015035,0.0000343199,0.001101916,0.0004168983],"genre_scores_gemma":[0.1446739,0.0001692563,0.8528836,0.0001207153,0.00002840859,0.0003603449,0.0002162743,0.0003430029,0.001204561],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01670027,"threshold_uncertainty_score":0.08832049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2230894389177613,"score_gpt":0.4513083604494997,"score_spread":0.2282189215317384,"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."}}