{"id":"W3198482522","doi":"10.4230/lipics.esa.2021.46","title":"Space Efficient Two-Dimensional Orthogonal Colored Range Counting","year":2021,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Rectangle; Space (punctuation); Combinatorics; Mathematics; Multiplication (music); Linear space; Matrix (chemical analysis); Colored; Range (aeronautics); Set (abstract data type); Discrete mathematics; Upper and lower bounds; Algorithm; Computer science; 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":[0.001745259,0.001083457,0.0017311,0.001298873,0.001046447,0.003218992,0.003989969,0.001526852,0.00925118],"category_scores_gemma":[0.009832845,0.000482662,0.001300523,0.004362672,0.001311745,0.006423874,0.004666863,0.001593516,0.002148651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504309,"about_ca_system_score_gemma":0.002652616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002802723,"about_ca_topic_score_gemma":0.003681408,"domain_scores_codex":[0.9953074,0.000900161,0.0003467959,0.0008283354,0.001627442,0.0009898973],"domain_scores_gemma":[0.9939288,0.002127563,0.000423079,0.002460172,0.0007715331,0.0002887906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001416343,0.0008223963,0.002994922,0.0006360874,0.0001260113,0.0003328455,0.0003860844,0.1560533,0.0467751,0.179532,0.03025944,0.5806655],"study_design_scores_gemma":[0.000257951,0.0002633851,0.0006661745,0.00004152939,0.00004542511,0.0004323708,0.0002228143,0.8614592,0.03197139,0.09449217,0.01005756,0.0000900593],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04832909,0.0003783768,0.9330956,0.0006707276,0.0001486142,0.000265398,0.0005649262,0.004396627,0.01215054],"genre_scores_gemma":[0.3928981,0.0002292312,0.5975418,0.0004619407,0.00009857379,0.0004469343,0.001725589,0.0004380479,0.006159749],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00925118,"threshold_uncertainty_score":0.03094828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382408289740403,"score_gpt":0.2761275067103163,"score_spread":0.2623034238129122,"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."}}