{"id":"W4362606931","doi":"10.36227/techrxiv.22340764","title":"Generalized Inverse Matrix Construction for Code Based Cryptography","year":2023,"lang":"en","type":"preprint","venue":"","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Gaussian elimination; McEliece cryptosystem; Mathematics; Cryptosystem; Inverse; Cryptography; Decoding methods; Matrix (chemical analysis); Square matrix; Moore–Penrose pseudoinverse; Generalized inverse; Binary number; Algorithm; Discrete mathematics; Algebra over a field; Theoretical computer science; Arithmetic; Computer science; Pure mathematics; Symmetric matrix; Gaussian; Eigenvalues and eigenvectors","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":[0.0004030064,0.000462765,0.0003861941,0.0008870346,0.0005460925,0.0008396836,0.0004803192,0.0005026124,0.004513365],"category_scores_gemma":[0.001619786,0.000263011,0.0004617568,0.0008791839,0.0008935662,0.0009777369,0.0009022231,0.001116125,0.002013973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004697604,"about_ca_system_score_gemma":0.0008337835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005748324,"about_ca_topic_score_gemma":0.0006463422,"domain_scores_codex":[0.9993377,0.0002027183,0.00002156142,0.00006684161,0.0003192861,0.00005182004],"domain_scores_gemma":[0.9993864,0.0001998951,0.00004933676,0.0001815454,0.0001572579,0.00002558615],"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":[0.00009643439,0.00007084471,0.0002953442,0.0001916503,0.00002918061,0.0001668119,0.0001889279,0.05159605,0.03199738,0.6157903,0.007378659,0.2921984],"study_design_scores_gemma":[0.00005134299,0.0001453378,0.0002942417,0.00006663975,0.00002139972,0.0006501051,0.00006572533,0.4404973,0.05004786,0.4546166,0.05347423,0.00006919472],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009994822,0.0004511755,0.9786702,0.0002102024,0.0001218049,0.00006837118,0.00005091101,0.0005360338,0.009896479],"genre_scores_gemma":[0.1936173,0.0007209478,0.791899,0.0001909697,0.0001448923,0.0001795069,0.0002222401,0.0002414951,0.01278362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004513365,"threshold_uncertainty_score":0.01509869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02789132392455706,"score_gpt":0.2536716368298101,"score_spread":0.225780312905253,"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."}}