{"id":"W4396892532","doi":"10.1145/3651599","title":"Fast Matrix Multiplication for Query Processing","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Matrix multiplication; Multiplication (music); Query optimization; Matrix (chemical analysis); Arithmetic; Information retrieval; Mathematics; Physics; Chemistry; Combinatorics","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0006397471,0.000100074,0.0001250934,0.00007674519,0.00006897109,0.0002134123,0.006954094,0.00002596887,5.024006e-7],"category_scores_gemma":[0.00007286244,0.00007209273,0.0000510107,0.0004465298,0.00002587648,0.0006272839,0.003342333,0.0000578873,0.000004922032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001724117,"about_ca_system_score_gemma":0.00001450509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000302766,"about_ca_topic_score_gemma":9.123264e-8,"domain_scores_codex":[0.998865,0.000003572121,0.0002753411,0.0004196207,0.0002926524,0.0001437933],"domain_scores_gemma":[0.998528,0.00005096576,0.0001957663,0.00110377,0.0001020981,0.00001942123],"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":[0.00004590833,0.0002609143,0.0005977541,0.01548317,0.0002819637,8.581595e-7,0.0006807054,0.0004227698,0.00335974,0.4684806,0.1261558,0.3842298],"study_design_scores_gemma":[0.0006698997,0.00017112,0.002027971,0.005250718,0.0001521714,0.000006769897,0.0004070881,0.8515188,0.004497035,0.03049108,0.1044022,0.000405133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03083707,0.001912696,0.9302827,0.01765155,0.00148777,0.003493401,0.0004712887,0.0008706589,0.0129929],"genre_scores_gemma":[0.8862575,0.00001919905,0.1128635,0.00003036093,0.00006922441,0.00002613004,0.00003003821,0.0000109605,0.0006930982],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8554204,"threshold_uncertainty_score":0.9984187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0612702140294622,"score_gpt":0.3339377198722386,"score_spread":0.2726675058427764,"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."}}