{"id":"W3149546047","doi":"10.1109/ideas.2007.4318110","title":"The LBF R-tree: Efficient Multidimensional Indexing with Graceful Degradation","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Search engine indexing; Computer science; Exploit; Range query (database); Tree (set theory); Curse of dimensionality; Data mining; R-tree; Data structure; Range (aeronautics); Theoretical computer science; Web search query; Information retrieval; Search engine; Artificial intelligence; Sargable; Mathematics; Spatial analysis; Spatial 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":[0.0007558857,0.00008350167,0.00004829458,0.00006015243,0.000312588,0.0001887185,0.0004783106,0.00001556167,0.000005146394],"category_scores_gemma":[0.00001433281,0.00004479757,0.0000185846,0.000345483,0.00003969218,0.0002981023,0.0002567323,0.00006948664,0.00005150095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002107554,"about_ca_system_score_gemma":0.00001580886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002539513,"about_ca_topic_score_gemma":0.0001206492,"domain_scores_codex":[0.9989871,0.00001525397,0.0001284166,0.000231037,0.000388528,0.0002496135],"domain_scores_gemma":[0.9993345,0.0001387476,0.00005122985,0.0003738237,0.00005181958,0.0000499417],"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":[0.00001569677,0.00008016256,0.001230574,0.000002761559,0.00002188814,0.00002610136,0.0001138169,0.0005956228,0.0001724283,0.4883265,0.001928463,0.5074859],"study_design_scores_gemma":[0.001048444,0.0001471349,0.04971343,0.00002764487,0.00001165958,0.00001875642,0.0003388612,0.845717,0.005720786,0.0007115078,0.09611398,0.0004308314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02385374,0.00002794018,0.9676623,0.0008490716,0.0002175279,0.0001290794,3.406321e-7,0.000119467,0.007140581],"genre_scores_gemma":[0.6190305,0.000008136625,0.3717664,0.0006122216,0.0001012231,0.000008044175,0.00001684943,0.00001158074,0.008445059],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8451213,"threshold_uncertainty_score":0.2404206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009359691985560319,"score_gpt":0.2260400124968523,"score_spread":0.2166803205112919,"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."}}