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Record W3122781609 · doi:10.48550/arxiv.math/0606615

Superprocesses with Dependent Spatial Motion and General Branching\n Densities

2006· preprint· W3122781609 on OpenAlexaff
Donald A. Dawson, Zenghu Li, Hao Wang

Bibliographic record

VenuearXiv (Cornell University) · 2006
Typepreprint
Language
FieldMathematics
TopicStochastic processes and statistical mechanics
Canadian institutionsCarleton University
Fundersnot available
KeywordsMartingale (probability theory)MathematicsBrownian motionBounded functionLimit of a sequenceStatistical physicsParticle systemDiffusion processMathematical analysisBranching (polymer chemistry)Pure mathematicsLimit (mathematics)PhysicsApplied mathematicsStatistics

Abstract

fetched live from OpenAlex

We construct a class of superprocesses by taking the high density limit of a\nsequence of interacting-branching particle systems. The spatial motion of the\nsuperprocess is determined by a system of interacting diffusions, the branching\ndensity is given by an arbitrary bounded non-negative Borel function, and the\nsuperprocess is characterized by a martingale problem as a diffusion process\nwith state space $M(\\IR)$, improving and extending considerably the\nconstruction of Wang (1997, 1998). It is then proved in a special case that a\nsuitable rescaled process of the superprocess converges to the usual super\nBrownian motion. An extension to measure-valued branching catalysts is also\ndiscussed.\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.

How this classification was reachedexpand

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.595
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.047
GPT teacher head0.189
Teacher spread0.141 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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