Towards Digital Twins of the Oceans: The Potential of Machine Learning for Monitoring the Impacts of Offshore Wind Farms on Marine Environments.

Janina Schneider, André Klüner, Oliver Zielinski

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Toward sustainable outcomes for offshore wind and biodiversity in the digital era: Principles for collaborative digital ecosystem-based governance.iScience · 2026
Review

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

3 authors.

Janina SchneiderResearch Department Marine Perception, German Research Center for Artificial Intelligence, Marie-Curie-Straße 1, 26129 Oldenburg, Germany.ORCID 0000-0001-7477-7662

André KlünerResearch Department Marine Perception, German Research Center for Artificial Intelligence, Marie-Curie-Straße 1, 26129 Oldenburg, Germany.ORCID 0000-0003-1027-1763

Oliver ZielinskiResearch Department Marine Perception, German Research Center for Artificial Intelligence, Marie-Curie-Straße 1, 26129 Oldenburg, Germany.ORCID 0000-0002-6018-5030

Funding

European Space Agency AI4DTEMinistry for Science and Culture, Lower Saxony, Germany (Niedersächsisches Vorab) ZN3480

6 · The paper itself

Abstract

With an increasing number of offshore wind farms, monitoring and evaluating the effects of the wind turbines on the marine environment have become important tasks. Here we conducted a feasibility study with the focus on monitoring these effects by utilizing different machine learning methods. A multi-source dataset for a study site in the North Sea is created by combining satellite data, local in situ data and a hydrodynamic model. The machine learning algorithm DTWkNN, which is based on dynamic time warping and

Indexed as

anomaly detectionartificial intelligenceearth observationgreen energymarine ecosystemmissing value imputationNorth Searemote sensingSDG

Identifiers

PMID37430495

DOI10.3390/s23104581

PMCPMC10220890

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.