{"id":"W2139378575","doi":"10.1109/tcsi.2007.910539","title":"Design and Performance Analysis of a Unified, Reconfigurable HMAC-Hash Unit","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Hash-based message authentication code; Hash function; SHA-2; MD5; Cryptographic hash function; Computer science; Secure Hash Algorithm; Hash chain; Message authentication code; Double hashing; MDC-2; Theoretical computer science; Algorithm; Cryptography; Programming language","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":[0.001016664,0.0001456288,0.0002997621,0.0006688917,0.0003038556,0.0001037568,0.00017912,0.00007574485,0.00001939147],"category_scores_gemma":[0.000002407727,0.0001348669,0.00008584926,0.001362652,0.00008897224,0.0002129433,0.000001253354,0.0001092051,8.163793e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001897914,"about_ca_system_score_gemma":0.00004192975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001586749,"about_ca_topic_score_gemma":0.00009362175,"domain_scores_codex":[0.9986845,0.0001029563,0.0003905545,0.0003278531,0.0002482873,0.0002458995],"domain_scores_gemma":[0.9990928,0.0001832401,0.0001192674,0.0003630407,0.00009147234,0.0001502138],"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":[0.0001064001,0.0005295652,0.003393719,0.0005632315,0.004338807,0.00003673317,0.01326317,0.0661271,0.0552613,0.0387712,0.00007263391,0.8175361],"study_design_scores_gemma":[0.005238953,0.00258787,0.05397914,0.0004934932,0.002763351,0.0003564845,0.008782212,0.8676187,0.04765563,0.0003523862,0.007914179,0.002257634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2544174,0.000156962,0.7442366,0.00003109845,0.0001638535,0.000232642,0.000008639104,0.00003544631,0.0007172786],"genre_scores_gemma":[0.9988964,0.0002799504,0.0006022296,0.00003726466,0.000006929592,0.00001412801,0.000001973734,0.000007012461,0.0001540939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8152785,"threshold_uncertainty_score":0.5499712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03355543759429658,"score_gpt":0.2532406661559629,"score_spread":0.2196852285616663,"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."}}