{"id":"W2506792106","doi":"10.4230/lipics.socg.2016.28","title":"Two Approaches to Building Time-Windowed Geometric Data Structures","year":2016,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ackermann function; Mathematics; Combinatorics; Intersection (aeronautics); Algorithm; Convex hull; Time complexity; Sequence (biology); Computational geometry; Binary logarithm; Data structure; Discrete mathematics; Computer science; Inverse; Regular polygon; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008939783,0.0003491169,0.0003545672,0.0008754652,0.0003676488,0.0005724386,0.002712669,0.0001166482,0.00003934642],"category_scores_gemma":[0.0003552264,0.0002569153,0.000119924,0.00130893,0.00005361882,0.003040876,0.001602507,0.000159847,0.0002971851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001200128,"about_ca_system_score_gemma":0.0001170718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005055943,"about_ca_topic_score_gemma":0.000003333645,"domain_scores_codex":[0.9972425,0.00004719237,0.0008453709,0.0005337889,0.0006631923,0.0006679509],"domain_scores_gemma":[0.9972863,0.0003626234,0.0003044791,0.001553288,0.0001998682,0.0002934697],"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":[0.0001621243,0.0003723206,0.002659876,0.0002954201,0.000395787,0.000007174871,0.003082167,0.008179816,0.002037309,0.1530916,0.0302745,0.7994419],"study_design_scores_gemma":[0.009811664,0.0007610759,0.007737921,0.0002871797,0.0001024869,0.0002256638,0.0002294815,0.6127625,0.02058551,0.01996914,0.3250309,0.002496519],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07472266,0.00004359239,0.920981,0.0008831079,0.0006583582,0.000841681,0.0003693582,0.0002125693,0.001287699],"genre_scores_gemma":[0.6774864,0.000007053653,0.3200735,0.0009903387,0.0003892799,0.00006269259,0.0004619161,0.00002926323,0.0004996043],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7969453,"threshold_uncertainty_score":0.9999883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1046541354309391,"score_gpt":0.2871792587017805,"score_spread":0.1825251232708414,"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."}}