Evidence map›Paper›PMID 42875498›Full record

ArticleNature2026

Advancing subseasonal forecasting with machine learning.

Hannah Guan, Soukayna Mouatadid, Paulo Orenstein, Judah Cohen, Haiyu Dong, Zekun Ni, Jeremy Berman, Genevieve Flaspohler, Alex Lu, Jakob Schloer and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Hannah Guan *Microsoft Research, Cambridge, MA, USA.
Soukayna Mouatadid *University of Toronto, Toronto, Ontario, Canada.
Paulo OrensteinInstituto de Matemática Pura e Aplicada, Rio de Janeiro, Brazil.
Judah CohenDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. judah@mit.edu.ORCID http://orcid.org/0000-0002-7762-4482
Haiyu DongMicrosoft, Redmond, WA, USA.ORCID http://orcid.org/0009-0008-0986-8339
Zekun NiMicrosoft, Redmond, WA, USA.
Jeremy BermanMicrosoft, Redmond, WA, USA.
Genevieve FlaspohlerRhiza Research, Oakland, CA, USA.
Alex LuMicrosoft Research, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-9568-3155
Jakob SchloerEuropean Centre for Medium-Range Weather Forecasts, Reading, UK.
Joshua TalibEuropean Centre for Medium-Range Weather Forecasts, Reading, UK.ORCID http://orcid.org/0000-0002-4183-1973
Jonathan A WeynMicrosoft, Redmond, WA, USA.ORCID http://orcid.org/0000-0002-4789-7594
Lester MackeyMicrosoft Research, Cambridge, MA, USA. lmackey@microsoft.com.ORCID http://orcid.org/0000-0002-1102-0387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy and prepare for weather extremes

Identifiers

PMID42875498

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.