{"id":"W4386629830","doi":"10.1002/spe.3261","title":"Transcoding unicode characters with AVX‐512 instructions","year":2023,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Transcoding; JavaScript; Unicode; Parallel computing; Set (abstract data type); Programming language; Operating system; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00020666,0.0001202988,0.0001083848,0.0001298797,0.0003907193,0.0002402788,0.0003668357,0.00004492161,0.000003202571],"category_scores_gemma":[0.0002279536,0.0001053808,0.00002100266,0.0008452446,0.00009014842,0.001912678,0.0001124335,0.0001514673,0.00001941959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001659767,"about_ca_system_score_gemma":0.00005418792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002990839,"about_ca_topic_score_gemma":0.000001942677,"domain_scores_codex":[0.9989764,0.00005776721,0.0001454262,0.0003645516,0.0002063126,0.0002495448],"domain_scores_gemma":[0.9991428,0.0002518483,0.00009292717,0.0003260784,0.00009345122,0.00009289259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002841977,0.0004349065,0.01485918,0.000193211,0.0002085396,0.0006240706,0.2707978,0.01056447,0.002879336,0.1278431,0.005190792,0.5661204],"study_design_scores_gemma":[0.005067345,0.002391817,0.03201038,0.001175824,0.0001859727,0.005083809,0.04092206,0.3206822,0.02817529,0.01045069,0.5476583,0.006196291],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05866742,0.00007019651,0.9359766,0.002657917,0.0001769854,0.0001116634,0.00000102152,0.001802381,0.0005357762],"genre_scores_gemma":[0.6242959,0.0004932426,0.3740661,0.0008155137,0.00003579161,0.00005076347,0.000003914703,0.00001230242,0.0002265132],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5656285,"threshold_uncertainty_score":0.4297302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01945352153319082,"score_gpt":0.2839492299920069,"score_spread":0.2644957084588161,"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."}}