{"id":"W4387736264","doi":"10.36227/techrxiv.24328879.v1","title":"Ordered Reliability Direct Error Pattern Testing Decoding Algorithm","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Decoding methods; Algorithm; Reliability (semiconductor); Computer science; Sequential decoding; List decoding; Product (mathematics); Berlekamp–Welch algorithm; Variety (cybernetics); Binary number; State (computer science); Order (exchange); Concatenated error correction code; Mathematics; Block code; Arithmetic; Artificial intelligence; Power (physics)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001617952,0.0004821451,0.0005743302,0.0002240795,0.0002876981,0.0006321443,0.002155542,0.0002879049,0.00004997637],"category_scores_gemma":[0.001358183,0.000431702,0.0002171007,0.0006266949,0.00004611909,0.0001707722,0.004871652,0.001406203,0.0003427203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121058,"about_ca_system_score_gemma":0.0002202756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003761415,"about_ca_topic_score_gemma":0.00005151599,"domain_scores_codex":[0.9961718,0.0002995091,0.0006091253,0.001702691,0.0005653488,0.0006514743],"domain_scores_gemma":[0.996479,0.000930556,0.0003149518,0.001836699,0.0002434826,0.0001952752],"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":[4.762152e-7,0.00005024857,0.00934661,0.0001411102,0.00003314856,0.00006648801,0.0002910508,0.01014978,0.000005964841,0.00004111957,0.001407768,0.9784662],"study_design_scores_gemma":[0.0001384653,0.00003703027,0.008500106,0.0001999399,0.00001153836,0.000009678196,0.00001436703,0.9861799,0.00004876238,0.003557079,0.0007586669,0.0005444253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002110132,0.00004801833,0.980586,0.002197343,0.003154763,0.0003333797,0.00001943771,0.003930139,0.007620804],"genre_scores_gemma":[0.0597858,0.000013524,0.9321929,0.0003182114,0.0006604317,0.00009897984,0.00004148258,0.00008138086,0.006807355],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9779218,"threshold_uncertainty_score":0.9998135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06243711614455985,"score_gpt":0.3092117905610186,"score_spread":0.2467746744164587,"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."}}