On the uniformity of the approximation for $r$-associated Stirling numbers of the second Kind
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The $r$-associated Stirling numbers of the second kind are a natural extension of Stirling numbers of the second kind. A combinatorial interpretation of $r$-associated Stirling numbers of the second kind is the number of ways to partition $n$ elements into $m$ subsets such that each subset contains at least $r$ elements. Calculating the associated Stirling numbers is typically done with a recurrence relation or a generating function that are computationally expensive or alternatively with a closed-form that is practical for only a limited parameter range. In 1994 Hennecart proposed an approximation for the $r$-associated Stirling numbers that is fast to compute, is amenable to analysis over a wide range of parameters, and is conjectured to be asymptotically tight. There are a few other approximations for the associated Stirling numbers, but none of them are as general as Hennecart's. However, until this work, Hennecart's approximation had been utilized without a proper justification due to the absence of a rigorous proof. This work provides a proof of the uniformity of the Hennecart approximation.
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.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it