Bibliographic record
Abstract
Transition asymptotics for reaction-diffusion in random media by G. B. Arous, S. Molchanov, and A. Ramirez Extreme value theory for random exponentials by L. V. Bogachev Singular continuous and dense point spectrum for sparse trees with finite dimensions by J. Breuer Some new estimates on the spectral shift function associated with random Schrodinger operators by J.-M. Combes, P. D. Hislop, and F. Klopp On phase transitions and limit theorems for homopolymers by M. Cranston and S. Molchanov Asymptotics of the Poincare functions by G. Derfel, P. J. Grabner, and F. Vogl Hamiltonian extension and eigenfunctions for a time dispersive dissipative string by A. Figotin and J. Schenker Localization at low energies for attractive Poisson random Schrodinger operators by F. Germinet, P. D. Hislop, and A. Klein On the influence of random perturbations on the propagation of waves described by a periodic Schrodinger operator by Y. A. Godin, S. Molchanov, and B. Vainberg Spectral theory of 1-D Schrodinger operators with unbounded potentials by A. Gordon, J. L. Holt, and S. Molchanov Fermi-Dirac generators and tests for randomness by A. Gordon, S. Molchanov, and J. Quinn The spectral problem, substitutions and iterated monodromy by R. Grigorchuk, D. Savchuk, and Z. Sunic On scattering of solitons for wave equation coupled to a particle by V. Imaykin, A. Komech, and B. Vainberg Purely absolutely continuous spectrum for some random Jacobi matrices by U. Kaluzhny and Y. Last The parabolic Anderson model and its universality classes by W. Konig An inverse problem for Gibbs fields by L. Koralov Hierarchical Anderson model by E. Kritchevski Integral representations of solutions of periodic elliptic equations by P. Kuchment Inverse spectral problems for Schrodinger operators with energy depending potentials by A. Laptev, R. Shterenberg, and V. Sukhanov Theory of point processes and some basic notions in energy level statistics by N. Minami On the law of addition of random matrices: Covariance and the central limit theorem for traces of resolvent by L. Pastur and V. Vasilchuk Green's functions of generalized Lapalcians by P. Poulin Orthogonal polynomials with exponentially decaying recursion coefficients by B. Simon Poisson statistics for eigenvalues: From random Schrodinger operators to random CMV matrices by M. Stoiciu.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".