{"id":"W2124120807","doi":"10.1016/j.comgeo.2009.08.001","title":"Data structures for range-aggregate extent queries","year":2013,"lang":"en","type":"article","venue":"Computational Geometry","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rectangle; Aggregate (composite); Range (aeronautics); Set (abstract data type); Point (geometry); Partition (number theory); Computational geometry; Mathematics; Function (biology); Plane (geometry); Data structure; Set function; Computer science; Line segment; Combinatorics; Algorithm; Discrete mathematics; Geometry","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":[0.002813939,0.001652304,0.002418788,0.003417851,0.001917361,0.00545043,0.003446825,0.002197305,0.02373577],"category_scores_gemma":[0.01647961,0.001453943,0.001648051,0.006951638,0.001685251,0.01249396,0.009253812,0.002934225,0.007466496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002117055,"about_ca_system_score_gemma":0.001837143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003034888,"about_ca_topic_score_gemma":0.003626501,"domain_scores_codex":[0.9958662,0.0004135134,0.0007353703,0.0005015412,0.001990058,0.0004933588],"domain_scores_gemma":[0.9878434,0.00313188,0.0006316841,0.006577183,0.001399956,0.0004159947],"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":[0.003183522,0.0005297922,0.01019822,0.001773917,0.000315128,0.0006171233,0.002264478,0.02834927,0.02564052,0.3203225,0.2080451,0.3987606],"study_design_scores_gemma":[0.0007769449,0.0003621992,0.00329925,0.0005063174,0.0002906877,0.000932952,0.001832013,0.1918586,0.05917903,0.4473389,0.2933263,0.00029671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04338932,0.002152508,0.8466201,0.002317887,0.0005304393,0.0007555696,0.02729037,0.05419301,0.02275067],"genre_scores_gemma":[0.4131114,0.001970987,0.4803114,0.00172766,0.0005451442,0.002123174,0.06629173,0.01280902,0.02110955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02373577,"threshold_uncertainty_score":0.07940406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04191183951615511,"score_gpt":0.290789303862651,"score_spread":0.2488774643464959,"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."}}