{"id":"W2284443012","doi":"10.1007/s12095-016-0208-3","title":"Character values of the Sidelnikov-Lempel-Cohn-Eastman sequences","year":2016,"lang":"en","type":"preprint","venue":"Cryptography and Communications","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Character (mathematics); Autocorrelation; Stream cipher; Cipher; Algorithm; Cryptography; Binary number; Mathematics; Sequence (biology); Computer science; Discrete mathematics; Arithmetic; Statistics; Encryption","routes":{"ca_aff":true,"ca_fund":true,"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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0006195752,0.0003158154,0.0003622575,0.0003303555,0.0006833759,0.0002187799,0.006819507,0.0002199239,0.00001659576],"category_scores_gemma":[0.0000393189,0.0002096574,0.000543879,0.0007228442,0.001504631,0.0002133475,0.005623914,0.0006303356,0.000004223646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001116222,"about_ca_system_score_gemma":0.0001201723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003030068,"about_ca_topic_score_gemma":0.00001991795,"domain_scores_codex":[0.9978185,0.0006127069,0.000504547,0.0004967466,0.0002900658,0.0002774566],"domain_scores_gemma":[0.9928015,0.0004778143,0.0005189154,0.00588484,0.0002178685,0.00009902632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005728182,0.0001099695,0.007914962,0.00006251503,0.0001611529,2.779597e-7,0.001761364,0.000001737085,0.001017129,0.9711236,0.0002465674,0.01759501],"study_design_scores_gemma":[0.0001682909,0.00003939007,0.02850661,0.0005874421,0.00007699249,0.000006997857,0.000117627,0.0001855047,0.001082181,0.9589887,0.009872191,0.0003681075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5468581,0.03919182,0.2721407,0.06426697,0.003840672,0.003569691,0.0006645363,0.00121013,0.06825739],"genre_scores_gemma":[0.9847535,0.002235428,0.01238162,0.0003965583,0.00005601863,0.0001254429,0.00001014923,0.0000144732,0.00002678737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4378955,"threshold_uncertainty_score":0.9985541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02833204586572379,"score_gpt":0.2651129283421842,"score_spread":0.2367808824764604,"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."}}