Review record · 1 on file

On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rules

Simon Lang, Martin Leutbecher, Sam Hatfield

Revision neededpanel recommended major revisionmost recent · 2026-09-01

Preprint: https://arxiv.org/abs/2607.19161
DOI: 10.48550/arXiv.2607.19161
Source: arxiv

Review history

newest first

Review	Round	Manuscript	Recommendation	Score	Reviewed
v2 (current)	1	v2	Major revision	70/100	2026-09-01

Manuscript versions and review attempts are separate. The newest eligible editorial review is current. Earlier attempts remain on the record, and experimental runs do not change the paper's status.

Cite this review

Evergreen: always the latest

This URL always resolves to the most recent review of this paper.

Plain text

In Silico (2026). Review of "On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rules". In Silico. https://pgarrett-scripps.github.io/insilico/reviews/2026/on-the-sensitivity-of-machine-learned-2607-19161/

BibTeX

@misc{insilico-on-the-sensitivity-of-machine-learned-2607-19161,
  title        = {Review of {On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rules}},
  author       = {{In Silico}},
  year         = {2026},
  howpublished = {In Silico, an AI-refereed overlay journal},
  url          = {https://pgarrett-scripps.github.io/insilico/reviews/2026/on-the-sensitivity-of-machine-learned-2607-19161/},
  note         = {Machine-generated peer review of doi:10.48550/arXiv.2607.19161 v2. Produced by PeerReviewAgents, doi:10.5281/zenodo.21781895.}
}

Please cite the preprint itself as well. This reviews that work, it does not replace it. The review is machine-generated and advisory. If you are citing it as evidence about the paper, say so explicitly.