arXiv — Machine Learning · · 3 min read

One pool, many targets: a conservation layer and what archival data can identify

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Computer Science > Machine Learning

arXiv:2610.00445 (cs)
[Submitted on 30 Sep 2026]

Title:One pool, many targets: a conservation layer and what archival data can identify

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Abstract:Pairwise guide--transcript scores do not enforce conservation of a finite guide-loaded RISC pool when they are interpreted independently as occupancies. We formulate a differentiable scalar equilibrium layer: one conservation equation with a unique positive root and exact implicit gradients. It yields a redistribution theorem, a qualified high-resource limit, an analysis of the retrieval approximation, and a conditional rank-invariance result: within one construct at one dose, rankings by fractional occupancy cannot distinguish equilibrium from independent scoring. We therefore audit the two experiments that proposition leaves open, dose and cross-context, on archival off-target data. Corrected thermodynamic affinities associate weakly with measured repression in the direction a working predictor requires, but a paired permutation test and a construct-cluster bootstrap do not establish added predictive value from the coupling: what survives their differing permutation-null baselines is \GapNet{}, a descriptive \GapNetOverSE{} of the equilibrium association's cluster standard error. The dose fits are heterogeneous and frequently violate the model-implied exponent constraint, which is superlinear rather than sublinear, so these data do not identify the competition parameter. A saturable compression of the competitor set holds both accuracy targets on held-out guide families but is not faster at the size measured. The contribution is a reusable conservation operator and the experimental information needed to test it. The code for this study is available at this https URL.
Subjects: Machine Learning (cs.LG)
Cite as: arXiv:2610.00445 [cs.LG]
  (or arXiv:2610.00445v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2610.00445
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Zahra Khodagholi [view email]
[v1] Wed, 30 Sep 2026 17:50:12 UTC (2,061 KB)
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