Bibliographic record
Abstract
Invariants for finite dimensional groups in vertex operator algebras associated to basic representations of affine algebras by A. Baker and H. Tamanoi Transformation laws for theta functions by C. Dong and G. Mason Algebro-geometric isomonodromic deformations linking Hauptmoduls: Variation of the mirror map by C. F. Doran On McKay's connection between the affine $E_8$ diagram and the monster by G. Glauberman and S. P. Norton Sylow 2-subgroups of simple groups by K. Harada and M. L. Lang Yoshida surfaces with Picard number $\rho \geq 17$ by W. L. Hoyt and C. F. Schwartz Hypergeometric modular forms and supersingular elliptic curves by M. Kaneko and N. Todaka Fusion rules for ternary and $\mathbb{Z}_2 \times \mathbb{Z}_2$ code vertex operator algebras by C. H. Lam The regular representations and the $A_{n}(V)$-algebras by H. Li Linear dependencies among completely replicable functions by J. McKay Arithmetic semistable elliptic surfaces by J. McKay and A. Sebbar Modular invariance of trace functions on VOAs in many variables by M. Miyamoto The mirror map for a family of $K$3 surfaces induced from the simplest 3-dimensional reflexive polytope by N. Narumiya and H. Shiga From moonshine to the monster by S. Norton Hypergeometric functions and non-associative algebras by Y. Ohyama Extended affine root systems. V. Elliptic eta-products and their Dirichlet series by K. Saito Deflating infinite Coxeter groups to finite groups by C. S. Simons Genus two meromorphic conformal field theory by M. P. Tuite Picard-Fuchs equations of some families of elliptic curves by H. Verrill.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.225 | 0.041 |
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".