{"id":"W4297283065","doi":"10.1007/978-3-031-17718-7_7","title":"Performance Evaluation of Embedded Time Series Indexes Using Bitmaps, Partitioning, and Trees","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Search engine indexing; Bitmap; Partition (number theory); Index (typography); Hash function; Database index; Data structure; Range query (database); Series (stratigraphy)","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":[0.001859168,0.0001622138,0.0002379151,0.00065443,0.0006214936,0.0001535402,0.0009358502,0.0000543702,0.00002769867],"category_scores_gemma":[0.00004334568,0.0001655964,0.00002309344,0.0003534254,0.000822023,0.01179143,0.002060141,0.0002052683,0.000004454162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001182955,"about_ca_system_score_gemma":0.0003618853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001933736,"about_ca_topic_score_gemma":0.0000111267,"domain_scores_codex":[0.9982899,0.00006358754,0.0006142256,0.0002228703,0.0006631478,0.0001462594],"domain_scores_gemma":[0.9976304,0.00008590558,0.0004900763,0.001281269,0.0004614296,0.0000508936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004818487,0.00001529138,0.0003508861,0.0000643861,0.0000100642,1.474909e-7,0.004007555,0.006317022,0.00004256451,0.794327,0.00005001618,0.1948103],"study_design_scores_gemma":[0.000252739,0.00007447196,0.001815937,0.0002388905,0.00001207824,0.00003807458,0.00004732186,0.9438639,0.00005050813,0.001590185,0.05177057,0.0002452954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04247208,0.005797598,0.6647664,0.00106914,0.00134271,0.00351968,0.000398503,0.0003955778,0.2802383],"genre_scores_gemma":[0.2841706,0.007893792,0.7057779,0.0003247066,0.0000688193,0.0001512868,0.0003716866,0.00002702045,0.001214189],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9375469,"threshold_uncertainty_score":0.85485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05660588909551979,"score_gpt":0.3088618256095822,"score_spread":0.2522559365140624,"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."}}