Evidence map›Paper›PMID 42719772›Full record

ArticleInnovation (Cambridge (Mass.))2026

Global cycling of dissolved organic carbon between seawater and sediments quantified using physics-based artificial intelligence.

Peyman Babakhani, Andrew W Dale, Clare Woulds, Oliver W Moore, Ke-Qing Xiao, Majid Sedighi, Mingyu Zhao, Xiaohui Chen, Tanapon Phenrat, Farhad Jazaei and 2 more

Abstract read
In one paragraph

Article in Innovation (Cambridge (Mass.)), 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

12 authors.

Peyman BabakhaniDepartment of Civil Engineering and Management, University of Manchester, Manchester M13 9PL, UK.
Andrew W DaleGEOMAR Helmholtz Centre for Ocean Research Kiel, Wischhofstrasse, 1-3, 24148 Kiel, Germany.
Clare WouldsSchool of Geography, University of Leeds, Leeds LS2 9JT, UK.
Oliver W MooreDepartment of Environment and Geography, University of York, York YO10 5DD, UK.
Ke-Qing XiaoState Key Lab of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Majid SedighiDepartment of Civil Engineering and Management, University of Manchester, Manchester M13 9PL, UK.
Mingyu ZhaoKey Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China.
Xiaohui ChenSchool of Civil Engineering, University of Leeds, Leeds LS2 9JT, UK.
Tanapon PhenratDepartment of Civil Engineering, Faculty of Engineering, Naresuan University, Phitsanulok 65000, Thailand.
Farhad JazaeiDepartment of Civil, Construction, and Environmental Engineering, University of Memphis, Memphis TN 38152, USA.
Lisa CurtiEarth Surface Science Institute, School of Earth, Environment and Sustainability, University of Leeds, Leeds LS2 9JT, UK.
Caroline L PeacockEarth Surface Science Institute, School of Earth, Environment and Sustainability, University of Leeds, Leeds LS2 9JT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The origin of dissolved organic carbon (DOC) in the ocean, which represents the largest active reservoir of exchangeable carbon on Earth, remains unknown due to the complexity of determining DOC exchange between marine sediments and seawater. Here, we emulate underlying processes of DOC dynamics using physics-based artificial intelligence (AI) to quantify DOC cycling and preservation in sediments at the global scale. We conclude that up to 11% of all particulate organic carbon deposited on the global seafloor returns to seawater as DOC following hydrolysis within the sediment, which is around half of the riverine DOC flux to the ocean. Around 50% of the total solid-phase organic carbon in the upper meter of sediments is formed through the sorption of DOC to minerals. Further, we show that the contribution of the abyssal plain to global DOC efflux and preservation, which is typically entirely overlooked in carbon cycle studies, is equivalent to half the contribution of the continental margins. This study also highlights the power of simpler AI algorithms compared to more complex models and extends the principle of parsimony in mathematical modeling to the context of physics-based AI.

Indexed as

dissolved organic carbonglobal carbon cyclemarine sedimentsphysics-based artificial intelligencereactive transport modelRTM

Identifiers

PMID42719772
PMCPMC13556315

What Socratic 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 Socratic graph.