{"id":"W2760759533","doi":"10.1145/3121050.3121086","title":"An Exploration of Serverless Architectures for Information Retrieval","year":2017,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; NoSQL; Cloud computing; Tree traversal; Server; Architecture; Service (business); World Wide Web; Database; Information retrieval; Scalability; 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":[0.0002588884,0.00004471683,0.00005980875,0.0000526001,0.0002189668,0.0002402551,0.000745364,0.00001928768,7.551163e-7],"category_scores_gemma":[0.00004001378,0.00003540086,0.00003061365,0.0000337372,0.00001807356,0.000204202,0.0001379124,0.00002340758,0.000002357226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006130771,"about_ca_system_score_gemma":0.000009786463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002924482,"about_ca_topic_score_gemma":0.000007082032,"domain_scores_codex":[0.9995635,0.00001258607,0.0001291312,0.00008491611,0.0001298101,0.00008011197],"domain_scores_gemma":[0.9991536,0.00001898519,0.0001495494,0.0005806987,0.00007214861,0.00002502699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006454439,0.00008794439,0.0006094552,0.0001424826,0.0000263915,4.78022e-7,0.005956684,0.1040374,0.0003445679,0.2426981,0.0004019002,0.6456301],"study_design_scores_gemma":[0.0003998324,0.0001947945,0.00802057,0.00001481183,0.000003377119,5.27083e-7,0.0001132869,0.9713419,0.006836272,0.01076465,0.002210949,0.00009901744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3535058,0.000001535891,0.6438728,0.0005329167,0.000113596,0.0001168306,5.406128e-7,0.0000518665,0.001804168],"genre_scores_gemma":[0.9783147,1.576804e-7,0.02148497,0.0000773987,0.0000408427,0.000002537523,0.000001484226,0.000001456804,0.00007646543],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8673046,"threshold_uncertainty_score":0.2316786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0371025985620931,"score_gpt":0.287803261842949,"score_spread":0.2507006632808559,"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."}}