Phase transitions for the distance of random walks with applications to genome rearrangements
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.
Bibliographic record
Abstract
We study phase transition phenomena for the distance of random walks on graphs. In particular, we show how this question relates to the theory of random graphs and to stochastic processes of coalescence and fragmentation. This question is also intimately connected to some problems in genome rearrangement. Biographical sketch Nathanael Berestycki was born in Paris on December 6, 1980. He studied mathematics successively at Lycee Henri IV, Ecole Normale Superieure de Cachan, and Universite Paris VI, before he moved to Cornell University first as a visitor and then as a full-time Ph.D. student. His thesis was cosupervised by Rick Durrett in Cornell and Jean-Francois Le Gall in E.N.S. Now aged 24, his first position will be at the University of British Columbia in Vancouver, Canada, as a postdoctoral fellow.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it