{"id":"W2198834745","doi":"","title":"Optimizing key-value stores for hybrid storage architectures","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); University of Toronto","funders":"","keywords":"Computer science; Key (lock); Associative array; Byte; Latency (audio); Database; Computer data storage; Throughput; Data access; Distributed computing; Operating system; Telecommunications","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":[0.0005882223,0.0006227019,0.0005016575,0.0004167469,0.0004764273,0.001440151,0.001321153,0.0005504959,0.00121512],"category_scores_gemma":[0.001673621,0.0004090485,0.0002287753,0.0009133131,0.0005080269,0.002825706,0.0007934984,0.0003921872,0.0002582432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001331799,"about_ca_system_score_gemma":0.0009454808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804173,"about_ca_topic_score_gemma":0.004428702,"domain_scores_codex":[0.9995233,0.00009270262,0.00003287397,0.00008124314,0.0001566809,0.0001132506],"domain_scores_gemma":[0.9990865,0.0004013774,0.0001088271,0.0001403051,0.0002110474,0.00005190968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003031208,0.0001389115,0.002838429,0.0001281691,0.00005003041,0.0001226362,0.00008257569,0.9255196,0.03182172,0.009490791,0.001560849,0.02794312],"study_design_scores_gemma":[0.00001116392,0.00006587461,0.0002905734,0.000002512721,0.00001139973,0.0000311118,0.00004269652,0.9915527,0.005497777,0.002130431,0.0003569766,0.00000683858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8054425,0.001083985,0.1872332,0.0003801164,0.0000465219,0.00008381507,0.0002173811,0.001009163,0.004503202],"genre_scores_gemma":[0.9704167,0.0001835732,0.02820231,0.00002898705,0.000009783686,0.00003393202,0.00006298671,0.00005214749,0.001009441],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001804173,"threshold_uncertainty_score":0.009662867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384769953238676,"score_gpt":0.253994088109063,"score_spread":0.2401463885766762,"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."}}