Bibliographic record
Abstract
decuplet, 203 baryon octet, 203 Betti number, 267 Bogomolny bound, 163 Bott periodicity theorem, 213 bounce instanton, 41 chiral Dirac matrices, 239 chiral Ward-Takahashi identities, 249 circulant matrix, 142 collective coordinate, 20 confinement, 155, 184 contour deformation, 53 cosmic string, 102 cotangent space, 260 coulomb gas, 183 covariant derivative, 168 de Rham cohomology, 266 Debye screening, 183 deformation of supersymmetric quantum mechanics, 274 determinant, 25 determinant calculation method, 29 dilute gas approximation, 23 dilute gas of instantons, 154 eigenvalue λ 0 , 33 energy splitting, 34 Euclidean Dirac action, 244 Euclidean path integral, 8 Euler characteristic, 267 exterior algebra, 261 exterior derivative, 262 Faddeev-Popov determinant, 176 Faddeev-Popov method, 174 fermion zero mode, 251 frustration, 139 Fujikawa method, 246 functional integral, 64 gauge fields in a box, 214 gauge fixing, 173 gauge theory integration measure, 180 Gell-Mann matrices, 208 Georgi-Glashow model, 157 Grassmann gaussian integral, 242 Grassmann integral, 242 Grassmann numbers, 241 gravitational bounce, 92 gravitational bounce action, 96 gravitational corrections, 90 Gribov ambiguity, 174
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.820 | 0.812 |
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".