{"id":"W4312887229","doi":"10.14778/3551793.3551857","title":"Tiresias","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Latency (audio); Search engine indexing; Adaptation (eye); Row; Parallel computing; Artificial intelligence; Database","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":[0.0003758941,0.00008353868,0.00009561672,0.00006255477,0.0003465475,0.00004825882,0.001846067,0.000008411911,0.00001811679],"category_scores_gemma":[0.00001921447,0.000059161,0.00009630411,0.0004230531,0.0000267365,0.00001570686,0.003287065,0.0001243659,0.000004590076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008160265,"about_ca_system_score_gemma":0.00001718053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000231161,"about_ca_topic_score_gemma":2.278121e-7,"domain_scores_codex":[0.9988766,0.000009451745,0.0001685213,0.000227768,0.000525398,0.0001923089],"domain_scores_gemma":[0.9995528,0.00002296322,0.0001539895,0.0002011213,0.00003733232,0.00003178046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002603245,0.000697724,0.00572013,0.0001817905,0.0001563848,0.000004422975,0.007254681,0.01032301,0.01249559,0.7906026,0.1172605,0.05527715],"study_design_scores_gemma":[0.002827678,0.001093885,0.01978599,0.0001784136,0.0000950201,0.0001827416,0.003288414,0.1483234,0.09244895,0.05874906,0.6718451,0.001181365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9055393,0.000254455,0.0006659423,0.01528104,0.001042623,0.0006137451,0.00000170788,0.0002774839,0.07632365],"genre_scores_gemma":[0.9950537,0.000001510419,0.001902577,0.0004166769,0.00003789088,0.00004420383,6.040225e-8,0.000005710271,0.002537682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7318535,"threshold_uncertainty_score":0.4097092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009267484417925695,"score_gpt":0.194806908339679,"score_spread":0.1855394239217533,"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."}}