{"id":"W1658056400","doi":"10.1142/s0129626412500089","title":"DETERMINISTIC SAMPLE SORT FOR GPUS","year":2012,"lang":"en","type":"article","venue":"Parallel Processing Letters","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Merge sort; sort; Computer science; Sorting algorithm; Parallel computing; Sorting; Sample (material); Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008071439,0.0005526746,0.0007612703,0.0005154234,0.0009315978,0.002135631,0.001707626,0.0007351748,0.009191922],"category_scores_gemma":[0.005219056,0.000363868,0.0006127727,0.001453209,0.0009047083,0.002592745,0.001903902,0.001419209,0.00176894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001684906,"about_ca_system_score_gemma":0.002980045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006479319,"about_ca_topic_score_gemma":0.009156344,"domain_scores_codex":[0.9978914,0.0003115124,0.0001354502,0.000347123,0.00100836,0.0003060705],"domain_scores_gemma":[0.9973597,0.0006678452,0.0001703896,0.00108918,0.0006016362,0.0001113064],"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":[0.001477926,0.0001955248,0.003305377,0.000519671,0.0001438873,0.0001888954,0.0002245804,0.2019381,0.03194714,0.3708692,0.04429526,0.3448944],"study_design_scores_gemma":[0.0001532328,0.0001300993,0.0005235864,0.00002813784,0.00003674713,0.0001454861,0.00005665534,0.8016429,0.02955446,0.1301644,0.03752044,0.00004374751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03097401,0.0004754303,0.9528952,0.0006051285,0.0002775259,0.0000881975,0.0005137905,0.005577154,0.008593625],"genre_scores_gemma":[0.4150953,0.0003711059,0.5735593,0.000562239,0.0001158646,0.0002521319,0.001109875,0.0008182109,0.008115897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009191922,"threshold_uncertainty_score":0.0307501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03016900520291681,"score_gpt":0.2870489943193223,"score_spread":0.2568799891164055,"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."}}