Bibliographic record
Abstract
Given a permutation $\pi=\pi_1\pi_2\cdots \pi_n \in S_n$, we say an index $i$ is a peak if $\pi_{i-1} < \pi_i > \pi_{i+1}$. Let $P(\pi)$ denote the set of peaks of $\pi$. Given any set $S$ of positive integers, define ${P_S(n)=\{\pi\in S_n:P(\pi)=S\}}$. Billey-Burdzy-Sagan showed that for all fixed subsets of positive integers $S$ and sufficiently large $n$, $|P_S(n)|=p_S(n)2^{n-|S|-1}$ for some polynomial $p_S(x)$ depending on $S$. They conjectured that the coefficients of $p_S(x)$ expanded in a binomial coefficient basis centered at $max(S)$ are all positive. We show that this is a consequence of a stronger conjecture that bounds the modulus of the roots of $p_S(x)$. Furthermore, we give an efficient explicit formula for peak polynomials in the binomial basis centered at $0$, which we use to identify many integer roots of peak polynomials along with certain inequalities and identities. Etant donné une permutation $\pi=\pi_1\pi_2\cdots \pi_n \in S_n$ du groupe symétrique, nous disons qu’un indice i est unsommet si $\pi_{i-1} < \pi_i > \pi_{i+1}$. Soit $P(\pi)$ l’ensemble des sommets de $\pi$. Billey-Burdzy-Sagan ont montré que,pour tout sous-ensemble d’entiers positifs S et n suffisamment grand, le nombre de permutations de $n$ éléments avecensemble de sommets $S$ est $|P_S(n)|=p_S(n)2^{n-|S|-1}$ pour un certain polynôme $p_S(x)$ dépendant de $S$.. Ils ont fait la conjectureque les coefficients du polynôme $p_S(x)$ exprimé dans une base de coefficients binomiaux centrée en $max(S)$ sont touspositifs. Nous montrons que cela découle d’une conjecture plus forte qui borne le module des racines du polynôme$p_S(x)$. De plus, nous donnons une formule explicite efficace pour les polynômes sommets dans la base binomialecentrée en $0$, que nous utilisons pour identifier plusieurs racines entières de polynômes sommets, ainsi que certainesinégalités et identités.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".