{"id":"W4394838676","doi":"10.4230/lipics.approx/random.2024.34","title":"Matrix Multiplication Reductions","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Matrix multiplication; Reduction (mathematics); Matrix (chemical analysis); Mathematics; Multiplication (music); Algorithm; Random matrix; Overhead (engineering); Product (mathematics); Discrete mathematics; Combinatorics; Computer science; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001928941,0.0001970747,0.0001523211,0.0003836023,0.0001568437,0.0001739199,0.001333078,0.000188537,0.00002580477],"category_scores_gemma":[0.0000129261,0.0002326136,0.0002602139,0.0009348305,0.0000841745,0.0001670099,0.002126101,0.0005646212,0.0003861237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009259064,"about_ca_system_score_gemma":0.0001000033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003460389,"about_ca_topic_score_gemma":0.000006735816,"domain_scores_codex":[0.9985969,0.0000851088,0.0001265615,0.0009359543,0.00005369537,0.0002017609],"domain_scores_gemma":[0.9984199,0.00005559083,0.00009551112,0.001247425,0.00008198536,0.00009958846],"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":[0.000006418125,0.00004224837,0.00006644105,0.00005121585,0.0000590626,0.00004417971,0.0001997072,0.01988802,0.0001053873,0.977441,0.0007699229,0.001326358],"study_design_scores_gemma":[0.00009314886,0.0000185211,0.0001412632,0.00007091235,0.00006914353,0.000007099736,0.00004305866,0.2034137,0.0001423941,0.7928267,0.002890415,0.0002836437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1718262,0.0002665427,0.816471,0.0005908388,0.001906138,0.0002806015,0.00001819914,0.001209357,0.007431122],"genre_scores_gemma":[0.9939394,0.00009357247,0.00277009,0.00002654131,0.0001169455,0.000001930343,0.000009044315,0.00001270206,0.003029766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8221133,"threshold_uncertainty_score":0.9485709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05783141494549967,"score_gpt":0.2019917898749169,"score_spread":0.1441603749294172,"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."}}