3049-4753

Machine Learning Earth

IOP Publishing

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Ordered by how many DOIs each fix touches — start here, not with every error at once.

1

Add abstracts to 51 articles

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High impact51 DOIs
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Low impact6 DOIs

DOIs for this ISSN

Showing the top 5 of 51 DOIs, ordered by correction priority.

# Title Missing Priority Citations
1 Deep learning meets teleconnections: improving S2S predictio… (10.1088/3049-4753/ade9c2)
Abstract
22.58 7
2 Global climate model bias correction using deep learning (10.1088/3049-4753/ade9c3)
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19.45 5
3 Physics informed neural networks for maritime energy systems… (10.1088/3049-4753/adfe73)
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17.47 4
4 Scalable deep fusion of spaceborne lidar and synthetic apert… (10.1088/3049-4753/ae2c01)
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15.05 3
5 Towards Generalized Hydrological Forecasting using Transform… (10.1088/3049-4753/ae81b8)
Abstract References
15.05 1
6 Ground motion modeling and epistemic uncertainty using condi… (10.1088/3049-4753/adcfa5)
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11.93 2
7 The need of explainability in low-carbon urban system design… (10.1088/3049-4753/adde60)
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11.93 2
8 Quantum neural networks for cloud cover parameterizations in… (10.1088/3049-4753/ae4981)
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11.93 2
9 Ensemble learning for uncertainty estimation with applicatio… (10.1088/3049-4753/add93b)
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7.53 1
10 Assimilation of diurnal satellite retrieval of sea surface t… (10.1088/3049-4753/adfb7e)
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7.53 1
11 Generative Lagrangian data assimilation for ocean dynamics u… (10.1088/3049-4753/ae0b70)
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7.53 1
12 Exploring the viability of a machine learning-based multimod… (10.1088/3049-4753/ae1980)
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7.53 1
13 Imitation or identification: limitations of deep learning in… (10.1088/3049-4753/ae2279)
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7.53 1
14 Multimodal atmospheric super-resolution with deep generative… (10.1088/3049-4753/ae286e)
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7.53 1
15 Spatial deep learning for PM <sub>2.5</s… (10.1088/3049-4753/ae3c12)
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7.53 1
16 DeepCut: adaptive neural network thresholds for precipitatio… (10.1088/3049-4753/ae5066)
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7.53 1
17 Assessing and explaining temporal deep learning models for w… (10.1088/3049-4753/ae5aa0)
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7.53 1
18 Graph-enhanced neural operator for missing velocities recons… (10.1088/3049-4753/adc934)
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0.00 0
19 Targeting bias in algorithm optimization improves reconstruc… (10.1088/3049-4753/adddc3)
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0.00 0
20 Editorial: Launching <i>Machine Learning: Earth</i>—a new fo… (10.1088/3049-4753/adeb8b)
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0.00 0
21 The AI Weather Quest: an international competition for sub-s… (10.1088/3049-4753/adf649)
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0.00 0
22 Modulation of tropical cyclogenesis on subseasonal-to-intera… (10.1088/3049-4753/adfd61)
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0.00 0
23 Machine learning subseasonal forecast model of summer precip… (10.1088/3049-4753/ae12f5)
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0.00 0
24 A deep learning approach for exploring the physical mechanis… (10.1088/3049-4753/ae1b07)
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0.00 0
25 ML-driven cross-calibration of microwave and infrared instru… (10.1088/3049-4753/ae1cce)
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0.00 0
26 Uncovering patterns of converging human-induced pressure on… (10.1088/3049-4753/ae2278)
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27 Machine learning insights for fire impacts on snow disappear… (10.1088/3049-4753/ae2a36)
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0.00 0
28 Calibration of climate model parameterizations using Bayesia… (10.1088/3049-4753/ae2edb)
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0.00 0
29 Creating a comprehensive cryoseismic catalog at Rhonegletsch… (10.1088/3049-4753/ae375b)
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0.00 0
30 AI-informed model-analogs for understanding subseasonal-to-s… (10.1088/3049-4753/ae4805)
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0.00 0
31 Zero-shot forecasting of streamflow using time series founda… (10.1088/3049-4753/ae4982)
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0.00 0
32 Assessment of power law limitations and hub-height wind spee… (10.1088/3049-4753/ae4c8d)
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0.00 0
33 Four low-level cloud regimes revealed by latent space analys… (10.1088/3049-4753/ae4e30)
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0.00 0
34 Am I confused or is this confusing?: Deep ensembles for ENSO… (10.1088/3049-4753/ae4fc0)
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35 Generative AI for seismic data enhancement: a novel workflow… (10.1088/3049-4753/ae5065)
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36 Fourier analysis of the physics of transfer learning for dat… (10.1088/3049-4753/ae510d)
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37 Predictability of precipitation extremes in the Western Unit… (10.1088/3049-4753/ae52fd)
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38 Improving deep learning for earthquake detection and localiz… (10.1088/3049-4753/ae611a)
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39 Machine learning of vertical fluxes by unresolved midlatitud… (10.1088/3049-4753/ae611b)
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40 Data-driven subgrid-scale turbulence parameterization: metho… (10.1088/3049-4753/ae6dbe)
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41 An interpretable latent space reveals changing dynamics of E… (10.1088/3049-4753/ae6e42)
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42 TeleViT1.0: teleconnection-informed vision transformers for… (10.1088/3049-4753/ae7088)
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43 How accurate are salinity measurements around Antarctica? A… (10.1088/3049-4753/ae7113)
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44 How far can we downscale? Resolution limits and physical int… (10.1088/3049-4753/ae7114)
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45 A deep learning bias-correction layer for land surface model… (10.1088/3049-4753/ae7115)
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46 Seasonal forecast of sea surface temperatures via Neural ODE… (10.1088/3049-4753/ae7447)
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47 Can deep learning outperform mechanistic modeling of peatlan… (10.1088/3049-4753/ae7726)
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48 Interpretable Neural Networks to Predict Momentum Fluxes of… (10.1088/3049-4753/ae7df2)
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49 Swift: An Autoregressive Consistency Model for Efficient Wea… (10.1088/3049-4753/ae802a)
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50 Data curation strategies for geospatial machine learning: A… (10.1088/3049-4753/ae8304)
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