Singularities in PDE and the Calculus of Variations
Bibliographic record
Abstract
Variational problems arising in biology by E. R. Alvarez-Buylla, M. Benitez, A. Chaos, Y. Cortes, G. Escalera-Santos, C. Espinosa, and P. Padilla On the Cauchy problem for phase and vortices in the parabolic Ginzburg-Landau equation by F. Bethuel, G. Orlandi, and D. Smets Nonlocal Cahn-Hilliard and isoperimetric problems: Periodic phase separation induced by competing long- and short-range interactions by R. Choksi On a generalized Ginzburg-Landau energy for superconducting/normal composite materials by T. Giorgi and H. Jadallah Global questions for map evolution equations by M. Guan, S. Gustafson, K. Kang, and T.-P. Tsai Pohozaev-type identities for an elliptic equation by R. Ignat Some remarks on Monge-Ampere functions by R. L. Jerrard Variational versus pde-based approaches in mathematical image processing by B. Kawohl On the energy of a Chern-Simons-Higgs vortex lattice by M. Kurzke and D. Spirn Some recent results about a class of singularly perturbed elliptic equations by A. Malchiodi The dipole problem for $H^{1/2}(\mathbb{S}^2 \mathbb{S}^1)$-maps and application by V. Millot Hodge decompositions, $\Gamma$-convergence and the Gross-Pitaevskii energy by A. Montero Bifurcation of vortex solutions to a Ginzburg-Landau equation in an annulus by Y. Morita An Allen-Cahn type problem with curvature modification by X. Ren Rare events, action minimization, and sharp interface limits by M. G. Westdickenberg The Gauss-Green theorem for weakly differentiable vector fields by W. P. Ziemer.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".