{"id":"W2903305323","doi":"10.1017/jpr.2019.52","title":"Sums of standard uniform random variables","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Probability","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Characterization (materials science); Dimension (graph theory); Aggregate (composite); Random variable; Marginal distribution; Set (abstract data type); Type (biology)","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":[0.001199066,0.00008990081,0.0003932512,0.00003939608,0.00003311777,0.00001412385,0.0001607997,0.00006028802,0.0008823367],"category_scores_gemma":[0.0004275112,0.00006813998,0.00009885463,0.0001742232,0.00008736537,0.00006145424,0.00002466031,0.0001550757,0.0000184338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000864262,"about_ca_system_score_gemma":0.00014215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.273138e-7,"about_ca_topic_score_gemma":7.469461e-7,"domain_scores_codex":[0.9986138,0.00002922913,0.0007907905,0.00009888512,0.0003525972,0.0001146619],"domain_scores_gemma":[0.9978798,0.0007789587,0.0005812461,0.0002464378,0.0004322848,0.00008129205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004793315,0.0001451258,0.0003255067,0.0001908232,0.00003376801,1.880995e-7,0.00008624107,0.0001200134,0.001103413,0.9952466,0.0009919109,0.001277011],"study_design_scores_gemma":[0.001957486,0.00008432361,0.00112738,0.00003064311,0.00005251031,0.000004924762,0.00008366405,0.0004977842,0.005164266,0.9893751,0.001544922,0.00007706501],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.394767,0.000009217275,0.5792197,0.0002537616,0.00008536541,0.0006888305,0.0001667324,0.00002207983,0.02478729],"genre_scores_gemma":[0.905974,0.000003159486,0.09393065,0.00002129734,0.00002130118,0.000007967144,0.000005736634,0.000006400128,0.00002946157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.511207,"threshold_uncertainty_score":0.9660968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03523335547101941,"score_gpt":0.3135361675358512,"score_spread":0.2783028120648318,"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."}}