The algebra of dual −1 Hahn polynomials and the Clebsch-Gordan problem of <i>sl</i>−1(2)
Bibliographic record
Abstract
The algebra \documentclass[12pt]{minimal}\begin{document}$\mathcal {H}$\end{document}H of the dual −1 Hahn polynomials is derived and shown to arise in the Clebsch-Gordan problem of sl−1(2). The dual −1 Hahn polynomials are the bispectral polynomials of a discrete argument obtained from the q → −1 limit of the dual q-Hahn polynomials. The Hopf algebra sl−1(2) has four generators including an involution, it is also a q → −1 limit of the quantum algebra slq(2) and furthermore, the dynamical algebra of the parabose oscillator. The algebra \documentclass[12pt]{minimal}\begin{document}$\mathcal {H}$\end{document}H, a two-parameter generalization of \documentclass[12pt]{minimal}\begin{document}$\mathfrak {u}(2)$\end{document}u(2) with an involution as additional generator, is first derived from the recurrence relation of the −1 Hahn polynomials. It is then shown that \documentclass[12pt]{minimal}\begin{document}$\mathcal {H}$\end{document}H can be realized in terms of the generators of two added sl−1(2) algebras, so that the Clebsch-Gordan coefficients of sl−1(2) are dual −1 Hahn polynomials. An irreducible representation of \documentclass[12pt]{minimal}\begin{document}$\mathcal {H}$\end{document}H involving five-diagonal matrices and connected to the difference equation of the dual −1 Hahn polynomials is constructed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".