{"id":"W3201160209","doi":"10.1002/spe.3036","title":"Transcoding billions of Unicode characters per second with SIMD instructions","year":2021,"lang":"en","type":"preprint","venue":"Software Practice and Experience","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"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":"Transcoding; Computer science; SIMD; Unicode; Software; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000463704,0.0009337136,0.0004511078,0.001696234,0.0003917511,0.001010234,0.0007987192,0.0005296963,0.01215885],"category_scores_gemma":[0.004633658,0.0002502087,0.000344797,0.001756345,0.0005825909,0.001186615,0.001152601,0.0007689209,0.005258717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003994922,"about_ca_system_score_gemma":0.000363894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00113947,"about_ca_topic_score_gemma":0.001060635,"domain_scores_codex":[0.9994099,0.00005196973,0.00006338788,0.000088787,0.0003506791,0.00003534405],"domain_scores_gemma":[0.9979807,0.0005324446,0.00009412211,0.0005542192,0.0007771972,0.00006136359],"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":[0.0007774851,0.0001299958,0.001758711,0.000438122,0.000100646,0.0007074779,0.0005486435,0.02015535,0.124866,0.01979583,0.04309002,0.7876318],"study_design_scores_gemma":[0.0001270102,0.0002838195,0.002017649,0.0001769449,0.00009029589,0.001710787,0.0003489552,0.4198053,0.4146526,0.02784091,0.1328538,0.00009194625],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09833076,0.001847837,0.842979,0.000860233,0.001843743,0.0002386485,0.001805778,0.02907062,0.02302335],"genre_scores_gemma":[0.3538951,0.001062073,0.6126339,0.0005326933,0.0003994804,0.0003132558,0.004331911,0.002898053,0.02393346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01215885,"threshold_uncertainty_score":0.0406754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794266087902488,"score_gpt":0.2716954210409309,"score_spread":0.253752760161906,"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."}}