Evidence map›Paper›PMID 40188197›Full record

ArticleNature communications2025

Big data show idiosyncratic patterns and rates of geomorphic river mobility.

Richard J Boothroyd, Richard D Williams, Trevor B Hoey, Gary J Brierley, Pamela L M Tolentino, Esmael L Guardian, Juan C M O Reyes, Cathrine J Sabillo, Laura Quick, John E G Perez and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Richard J BoothroydSchool of Geographical and Earth Sciences, University of Glasgow, Glasgow, UK. richard.boothroyd@glasgow.ac.uk.ORCID http://orcid.org/0000-0001-9742-4229
Richard D WilliamsSchool of Geographical and Earth Sciences, University of Glasgow, Glasgow, UK.ORCID http://orcid.org/0000-0001-6067-1947
Trevor B HoeyDepartment of Civil and Environmental Engineering, Brunel University London, Uxbridge, UK.
Gary J BrierleySchool of Environment, University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0002-1310-1105
Pamela L M TolentinoSchool of Geographical and Earth Sciences, University of Glasgow, Glasgow, UK.
Esmael L GuardianNational Institute of Geological Sciences, University of the Philippines, Diliman, Philippines.
Juan C M O ReyesNational Institute of Geological Sciences, University of the Philippines, Diliman, Philippines.
Cathrine J SabilloNational Institute of Geological Sciences, University of the Philippines, Diliman, Philippines.
Laura QuickSchool of Geographical and Earth Sciences, University of Glasgow, Glasgow, UK.ORCID http://orcid.org/0000-0003-2725-4767
John E G PerezNational Institute of Geological Sciences, University of the Philippines, Diliman, Philippines.
Carlos P C DavidNational Institute of Geological Sciences, University of the Philippines, Diliman, Philippines.

Funding

RCUK | Natural Environment Research Council (NERC) NE/S003312/
6 · The paper itself

Abstract

Big data present unprecedented opportunities to test long-standing theories regarding patterns and rates of geomorphic river adjustments. Here, we use locational probabilities derived from Landsat imagery (1988-2019) to quantify the dynamics of 600 km

Identifiers

PMID40188197
PMCPMC11972300

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.