ArticleiScience2025
A deep-learning-based consistency test approach for Earth system models on HPC systems.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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
Evaluating climate consistency is a critically important step in the development and optimization of Earth system models (ESMs) on the high-performance computing (HPC) systems. We have developed an Earth system model deep-learning consistency test, referred to as ESM-DCT. The ESM-DCT is based on the unsupervised bidirectional gate recurrent unit-autoencoder (BGRU-AE) model to study the features from the ESM simulation ensembles and adopts the reconstruction errors to evaluate the consistency. We use the Community Earth System Model (CESM) on the new Sunway heterogeneous system to evaluate the ESM-DCT. The results show that the ESM-DCT can determine whether or not the new model simulations are statistically distinguishable from the original trusted ensembles in the case of the heterogeneous computing environment, compiling optimization option changes, and model parameter changes. Our ESM-DCT tool provides an efficient and objective approach for verifying the reliability of the development and optimization of ESMs on HPC systems.
Indexed as
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.