ArticleACS omega2026
No-Harm Missing-Friction Correction for Potential-of-Mean-Force-Matched Coarse Graining.
Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Potential-of-mean-force (PMF)-matched coarse graining (CG) can make a retained coordinate structurally correct but dynamically wrong. Eliminated bath degrees of freedom carry projected memory and friction that control response curves, relaxation times, kinetics, and transport. We ask whether the observable part of this missing friction can be recovered cheaply without harming generated dynamics. Residual-force fits and scalar rescalings alone cannot answer that question because they may expose the signal or improve one summary while worsening another. We distinguish the measured finite-window error between the high-resolution reference (labeled AA throughout) and CG dynamics from the component supported by residual-memory diagnostics, formulate that component as an observable projected-memory object, and approximate its consequence with a finite-history or surrogate candidate. The candidate is deployed only when held-out continuation rollouts improve both response-curve and relaxation-time errors. In two complete experiments, the fitted increment was added to the same detailed-balance PMF transition used as the uncorrected baseline. For C6 and C5 end-to-end distances, selected strength 0.10 retained PMF histogram L1 distances of 0.054 and 0.061, and the one-sided 5% lower bounds of both dynamical error reductions were positive. Separate precorrection diagnostics assigned acetone C-O to a richer state description and ethanol heavy-atom end-to-end to a finite memory kernel, so neither received the low-cost correction. The 13-coordinate breadth panel and diagnosis-informed tests provide breadth and selectivity evidence. Against a C6-calibrated scalar clock, the finite-history candidates improved both errors in 4/4 point-estimate comparisons versus 3/4 and gave 2.8 times the mean joint gain; experiment-specific uncertainty is reported separately. A distinct OpenFF 2.3.0/OpenMM surrogate showed the same point-estimate improvement on four molecules. The resulting reproducible, cost-bounded rule corrects only when structural and rollout evidence support correction.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.