{"id":"W2114206928","doi":"10.14778/2536206.2536214","title":"RACE","year":2013,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Speedup; Cache; Cloud computing; Parallel computing; Sequence (biology); Representation (politics); Multi-core processor; Contrast (vision); Scaling; Artificial intelligence; Operating system; Mathematics","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":[0.00217072,0.001869461,0.001642563,0.001634025,0.001786681,0.003657269,0.003750796,0.002077881,0.1181336],"category_scores_gemma":[0.007369138,0.001227321,0.002344924,0.00216683,0.0007137096,0.004000791,0.003410833,0.002426613,0.1113963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009541815,"about_ca_system_score_gemma":0.002516452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002326074,"about_ca_topic_score_gemma":0.002943098,"domain_scores_codex":[0.9966571,0.0004999171,0.0002630343,0.00115653,0.0009979099,0.0004255265],"domain_scores_gemma":[0.9967409,0.0007601096,0.0002536158,0.001272534,0.0007816441,0.0001912825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001449626,0.000239574,0.003421659,0.001350869,0.000209281,0.0003191179,0.0003345804,0.005621769,0.02081641,0.05013237,0.668868,0.2472367],"study_design_scores_gemma":[0.0002116657,0.0001989789,0.001296207,0.0001363124,0.0001110153,0.0005248499,0.00007459738,0.02455363,0.01734051,0.02458197,0.9308477,0.0001225458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01001114,0.002541669,0.4076104,0.00175393,0.002598414,0.0009108321,0.05837656,0.3551615,0.1610356],"genre_scores_gemma":[0.0857437,0.002641899,0.4533868,0.004722238,0.001070912,0.002517344,0.1891476,0.0688385,0.191931],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1181336,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006947487662152172,"score_gpt":0.195774613035835,"score_spread":0.1888271253736829,"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."}}