{"id":"W4386212980","doi":"10.36227/techrxiv.24038001","title":"Generalized Inverse Binary Matrix Construction for Public Key Cryptography Applications","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":"McEliece cryptosystem; Mathematics; Binary number; Inverse; Cryptography; Matrix (chemical analysis); Cryptosystem; Key (lock); Key generation; Discrete mathematics; Algorithm; Arithmetic; Combinatorics; Computer science","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":[0.0005752345,0.0005883303,0.0003798899,0.0007824755,0.000651619,0.0009456879,0.0004938135,0.0006810546,0.005471215],"category_scores_gemma":[0.001977872,0.0003073783,0.000558809,0.001078304,0.000925202,0.001343091,0.001266725,0.001707772,0.002822284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005340109,"about_ca_system_score_gemma":0.0007206508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002739989,"about_ca_topic_score_gemma":0.000341448,"domain_scores_codex":[0.9993444,0.0002049049,0.00002871756,0.0001057128,0.0002585944,0.00005762564],"domain_scores_gemma":[0.9993122,0.0002103338,0.00006618214,0.0002230767,0.0001544465,0.00003385357],"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":[0.0001162497,0.00006742723,0.0002955565,0.0002216298,0.0000178737,0.0001721808,0.000197198,0.01697449,0.02361681,0.7369841,0.006451903,0.2148845],"study_design_scores_gemma":[0.00006764574,0.0001997673,0.0004143889,0.0001136398,0.0000307653,0.0009825306,0.00009355369,0.1694269,0.0404174,0.6925574,0.09562685,0.00006908382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007628218,0.000879521,0.977037,0.0004252926,0.0002033859,0.00007741036,0.00005817053,0.0004252522,0.01326578],"genre_scores_gemma":[0.2567481,0.001821034,0.7213688,0.0003713991,0.0004328459,0.0002965054,0.0003618188,0.0002066686,0.01839278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005471215,"threshold_uncertainty_score":0.0183031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03228620764382252,"score_gpt":0.2516458305483331,"score_spread":0.2193596229045106,"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."}}