{"id":"W3210231509","doi":"10.23977/acss.2021.050116","title":"Parallel HAIFA Hashing Algorithm Based on Lorenz Chaos","year":2021,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hash function; Computer science; Double hashing; Cryptographic hash function; Rolling hash; Algorithm; MDC-2; CHAOS (operating system); Perfect hash function; SHA-2; Parallel computing; Cryptography; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006167242,0.0002854612,0.0004340719,0.000197545,0.000136837,0.0005388678,0.0005150419,0.00008811642,0.000007801818],"category_scores_gemma":[0.00002213372,0.0002679545,0.00008439505,0.000511666,0.00005177379,0.001109157,0.0001879491,0.0002457614,0.00002311031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007830805,"about_ca_system_score_gemma":0.00009401766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000356161,"about_ca_topic_score_gemma":0.00001216691,"domain_scores_codex":[0.9973941,0.0003253057,0.0005153719,0.0008353635,0.0005043419,0.0004255238],"domain_scores_gemma":[0.9984546,0.0004934609,0.0001762472,0.000589629,0.0001414247,0.000144639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001680072,0.0002065913,0.0004406901,0.0001905681,0.00001713171,0.0005600079,0.0003886399,0.5243887,0.0007050147,0.007068846,0.0003577063,0.4656593],"study_design_scores_gemma":[0.0008910797,0.0001899645,0.0001977374,0.0004894221,0.000003182523,0.00005422123,0.0000208557,0.9908009,0.0006119081,0.001151098,0.005261346,0.0003282643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001040628,0.006251975,0.989903,0.0004158785,0.001648674,0.0002585832,0.000006367523,0.0001423672,0.0003325492],"genre_scores_gemma":[0.5865433,0.0004357811,0.4099163,0.002004769,0.000826836,0.0001038386,0.00002388946,0.00003795189,0.0001073086],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5855027,"threshold_uncertainty_score":0.9999773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693963951106101,"score_gpt":0.2601476479360223,"score_spread":0.2432080084249613,"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."}}