{"id":"W2161306597","doi":"10.1109/icde.2007.368994","title":"Semantic Prefetching of Correlated Query Sequences","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Overhead (engineering); Distributed computing; Real-time computing; Database; Operating system","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":[0.0004262153,0.00007153758,0.0001235001,0.00006841075,0.0000503502,0.0000111022,0.0002256064,0.00002993193,0.00001353148],"category_scores_gemma":[0.00003437839,0.00005405876,0.00002995013,0.0002510297,0.00004042845,0.0005993082,0.0001141086,0.00006270393,0.00001780022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001149765,"about_ca_system_score_gemma":0.00003036156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003383035,"about_ca_topic_score_gemma":0.0001265077,"domain_scores_codex":[0.9992108,0.00001891697,0.000260951,0.0001751485,0.0001606841,0.0001735154],"domain_scores_gemma":[0.9993703,0.0001009735,0.0001003662,0.0003300842,0.00005242418,0.00004578632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006295826,0.00002934579,0.003222157,0.0000525711,0.00001653359,0.00003747947,0.000884088,0.0002140599,0.01441731,0.9592094,0.0001975638,0.02171321],"study_design_scores_gemma":[0.002475512,0.0009137618,0.0548385,0.00155934,0.00004775104,0.0007969942,0.004566262,0.138909,0.661009,0.0303538,0.1018118,0.002718301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06528296,0.0001140079,0.9259805,0.00004771491,0.0002816637,0.00006597288,0.000001334775,0.0001187857,0.008107046],"genre_scores_gemma":[0.8565446,0.000006763907,0.1428485,0.0000546901,0.00001934839,8.696475e-7,0.000001570175,0.000003087198,0.0005206773],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9288556,"threshold_uncertainty_score":0.2204452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254598630217663,"score_gpt":0.2554909880358043,"score_spread":0.2429450017336277,"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."}}