Coxeter Transformations, the McKay correspondence, and the Slodowy correspondence
Bibliographic record
Abstract
This talk was presented at Workshop "Spectral Methods in Representation Theory of Algebras and Applications to the Study of Rings of Singularities", 2008 (Banff, Canada). W. Ebeling established a connection between certain Poincare series, the Coxeter transformation C, and the corresponding affine Coxeter transformation C_a (in the context of the McKay correspondence). We consider the generalized Poincare series [\tilde{P}_G(t)]_0 for the case of multiply-laced diagrams(in the context of the McKay-Slodowy correspondence) and extend the Ebeling theorem for this case: [\tilde{P}_G(t)]_0 = X(t^2)/\tilde{X}(t^2), where X is the characteristic polynomial of the Coxeter transformation and \tilde{X} is the characteristic polynomial of the corresponding affine Coxeter transformation. We obtain that Poincare series coincide for pairs of diagrams obtained by folding: X (Γ) / X (\tilde{Γ}) = X (Γ^f) / X (\tilde{Γ}^f), where Γ is any (A, D, E type) Dynkin diagram, Γ is the extended Dynkin diagram, and the diagrams Γ^f and \tilde{Γ}^f are obtained by folding from Γ and \tilde{Γ}, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".