{"id":"W2169634760","doi":"10.1287/opre.48.2.308.12385","title":"Close-Point Spatial Tests and Their Application to Random Number Generators","year":2000,"lang":"en","type":"article","venue":"Operations Research","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Universität Salzburg","keywords":"Mathematics; Hypercube; Point process; Poisson point process; Torus; Poisson distribution; Square root; Unit square; Convergence (economics); Random number generation; Combinatorics; Transformation (genetics); Discrete mathematics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009132121,0.0001003268,0.0001019253,0.0001744693,0.0006468803,0.0004953162,0.0003238789,0.00004867339,0.0002582162],"category_scores_gemma":[0.00009347336,0.0000857466,0.0000251213,0.0009772244,0.00004406619,0.000388569,0.0001187921,0.0001553974,0.0007486853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005127806,"about_ca_system_score_gemma":0.0001454482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002660234,"about_ca_topic_score_gemma":0.0003910022,"domain_scores_codex":[0.9985324,0.0002374671,0.0001950953,0.0004289983,0.0003569227,0.0002491804],"domain_scores_gemma":[0.9989198,0.0001569566,0.000007272814,0.0003987623,0.0003490384,0.0001681975],"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":[0.00003299693,0.0001390274,0.0002181346,0.000006085036,0.00001465537,0.000002153873,0.001659356,0.06272031,0.01838267,0.03757841,0.003929847,0.8753164],"study_design_scores_gemma":[0.0008567222,0.0001341954,0.003810905,0.00001098944,0.000001979769,0.00003390021,0.00004322804,0.9188971,0.01958364,0.003838222,0.05253188,0.0002572774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3570335,0.00005287545,0.6358994,0.003482736,0.00006201578,0.0005533472,0.00000615553,0.00005743833,0.002852589],"genre_scores_gemma":[0.9699945,0.000036652,0.0272854,0.0002984986,0.0002615631,0.0002559566,0.00003026948,0.000008251769,0.001828935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8750591,"threshold_uncertainty_score":0.9623085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02618264260879456,"score_gpt":0.3463407485235901,"score_spread":0.3201581059147955,"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."}}