{"id":"W2948863035","doi":"10.1109/access.2019.2920917","title":"Parallel Multidimensional Lookahead Sorting Algorithm","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Speedup; Parallel computing; Overhead (engineering); Sorting; Sorting algorithm; Algorithm; Locality; Locality of reference; Parallel algorithm; CPU cache; Cache-oblivious algorithm; Cache; Cache algorithms","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":[0.0002002799,0.0001547929,0.0001809544,0.00007788851,0.0001303171,0.0002592648,0.001428132,0.00006771899,0.00008699542],"category_scores_gemma":[0.00001092803,0.0001281436,0.00006275775,0.0002305455,0.00002111891,0.001883343,0.0007164676,0.0001665314,0.000640877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002286385,"about_ca_system_score_gemma":0.0000581507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009439373,"about_ca_topic_score_gemma":0.000002567331,"domain_scores_codex":[0.9984526,0.0000389777,0.00025369,0.0005096608,0.0004032875,0.0003417537],"domain_scores_gemma":[0.9988456,0.00009186216,0.0001279985,0.0007374104,0.0000845811,0.0001125869],"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":[0.00002034563,0.0003224599,0.007666635,0.00004798041,0.00005542036,0.0001240247,0.0003400005,0.005890735,0.006808507,0.01248625,0.0215521,0.9446855],"study_design_scores_gemma":[0.0007819098,0.00004679139,0.00561926,0.00005957791,0.000003785273,0.00002638123,0.000007772974,0.9732164,0.004734242,0.002745312,0.01239964,0.0003589422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03848118,0.0001162059,0.9577966,0.0002413768,0.001802541,0.0001933884,0.000005891615,0.0001954662,0.001167399],"genre_scores_gemma":[0.2551503,0.00002926215,0.7411587,0.001461777,0.0004843049,0.0000293376,0.00002461833,0.00003091354,0.001630901],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9673256,"threshold_uncertainty_score":0.8237391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02410109803025487,"score_gpt":0.2965552075192603,"score_spread":0.2724541094890054,"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."}}