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Record W2577173787 · doi:10.48550/arxiv.1612.06751

Kernels of conditional determinantal measures and the proof of the\n Lyons-Peres Conjecture

2016· preprint· W2577173787 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) · 2016
Typepreprint
Language
FieldMathematics
TopicRandom Matrices and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEconometricsMathematical economicsMathematicsComputer science

Abstract

fetched live from OpenAlex

The main result of this paper, Theorem 1.5, establishes a conjecture of Lyons\nand Peres: for a determinantal point process governed by a reproducing kernel,\nthe system of kernels sampled at the particles of a random configuration is\ncomplete in the range of the kernel. A key step in the proof, Lemma 1.11,\nstates that conditioning on the configuration in a subset preserves the\ndeterminantal property, and the main Lemma 1.12 is a new local property for\nkernels of conditional point processes. In Theorem 1.7 we prove the triviality\nof the tail sigma-algebra for determinantal point processes governed by\nself-adjoint kernels.\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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.059
GPT teacher head0.203
Teacher spread0.144 · 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