Bibliographic record
Abstract
Lectures on Hilbert schemes by M. Lehn Lectures on instanton counting by H. Nakajima and K. Yoshioka Hyper-Kahler Nahm transforms by C. Bartocci and M. Jardim Instanton counting via affine Lie algebras. I. Equivariant $J$-functions of (affine) flag manifolds and Whittaker vectors by A. Braverman The Gysin map is compatible with mixed Hodge structures by M. A. A. de Cataldo and L. Migliorini Representations of fundamental groups of nonorientable 2-manifolds by N.-K. Ho and L. C. Jeffrey Mukai flops and derived categories. II by Y. Namikawa Fourier-Mukai number of a K3 surface by S. Hosono, B. H. Lian, K. Oguiso, and S.-T. Yau Derived equivalence of holomorphic symplectic manifolds by J. Sawon The affine stratification number and the moduli space of curves by M. Roth and R. Vakil Coherent sheaves on generic compact tori by M. Verbitsky The cohomology rings of Hilbert schemes via Jack polynomials by W.-P. Li, Z. Qin, and W. Wang.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".