{"id":"W4301206442","doi":"10.48550/arxiv.1010.1481","title":"A Simple Deterministic Reduction for the Gap Minimum Distance of Code\\n Problem","year":2010,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Reduction (mathematics); Mathematics; Constant (computer programming); Simple (philosophy); Coding (social sciences); Minimum distance; Code (set theory); Discrete mathematics; Finite field; Combinatorics; Algorithm; Computer science; Statistics; Geometry","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":[0.0008576949,0.000628245,0.0007348431,0.0002749355,0.001011614,0.0002324767,0.00428659,0.0005014232,0.00006693324],"category_scores_gemma":[0.0001264151,0.000621444,0.0007675755,0.001195566,0.001504772,0.0004440756,0.002020144,0.00119756,0.00001579648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001447858,"about_ca_system_score_gemma":0.0005348374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000167545,"about_ca_topic_score_gemma":0.0003019158,"domain_scores_codex":[0.996145,0.0002063511,0.0007222653,0.001938604,0.0002256848,0.0007621442],"domain_scores_gemma":[0.9941325,0.001024984,0.001183127,0.0027228,0.000701,0.0002356298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005700493,0.0007796065,0.0003875685,0.001114009,0.0004595465,0.00007418637,0.002078214,0.09840681,0.0008209699,0.8707991,0.0006126124,0.02389733],"study_design_scores_gemma":[0.0007128918,0.0002533841,0.0003068763,0.0001707274,0.0002775593,0.00002130725,0.0002516936,0.7162735,0.000381042,0.2746643,0.00612999,0.0005567827],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05571245,0.0001245758,0.9385639,0.0002253181,0.002492646,0.001821649,0.0002989648,0.0001048021,0.0006557254],"genre_scores_gemma":[0.9887174,0.0003161702,0.008957462,0.00003136747,0.0002896806,0.00001421868,0.00002364582,0.00003519506,0.001614904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9330049,"threshold_uncertainty_score":0.9996237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1028429319806388,"score_gpt":0.2227120243502111,"score_spread":0.1198690923695724,"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."}}