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Record W2963872945 · doi:10.48550/arxiv.1511.01618

[no title]

2015· article· en· W2963872945 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuearXiv (Cornell University) · 2015
Typearticle
Languageen
FieldMathematics
TopicStochastic processes and statistical mechanics
Canadian institutionsMcGill University
Fundersnot available
KeywordsLaw of the iterated logarithmMathematicsIterated logarithmMartingale (probability theory)Affine transformationLogarithmCombinatoricsIterated functionBall (mathematics)Bounded functionDiscrete mathematicsPure mathematicsApplied mathematicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

In two recent works, Kuba and Mahmoud (arXiv:1503.090691 and\narXiv:1509.09053) introduced the family of two-color affine balanced Polya urn\nschemes with multiple drawings. We show that, in large-index urns (urn index\nbetween $1/2$ and $1$) and triangular urns, the martingale tail sum for the\nnumber of balls of a given color admits both a Gaussian central limit theorem\nas well as a law of the iterated logarithm. The laws of the iterated logarithm\nare new even in the standard model when only one ball is drawn from the urn in\neach step (except for the classical Polya urn model). Finally, we prove that\nthe martingale limits exhibit densities (bounded under suitable assumptions)\nand exponentially decaying tails. Applications are given in the context of node\ndegrees in random linear recursive trees and random circuits.\n

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.272
GPT teacher head0.235
Teacher spread0.037 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it