Evidence map›Paper›PMID 41419743›Full record

ArticleScientific data2025

Harmonized geospatial data to evaluate the Electric Distribution Networks in the US Northeast.

Bernat Salbanya, Jordi Nin, Ramon Gras Alomà

Abstract read
In one paragraph

Article in Scientific data, 2025. 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

3 authors.

Bernat Salbanya *TBS Business School, Toulouse, Occitanie, France. b.salbanya@tbs-education.es.ORCID http://orcid.org/0000-0002-8270-4348
Jordi Nin *Universitat Ramon Llull, ESADE, Barcelona, Catalonia, Spain.ORCID http://orcid.org/0000-0002-9659-2762
Ramon Gras Alomà *Harvard University, SEAS, Cambridge, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable, open-access data on electric distribution networks is crucial for advancing energy equity, enhancing infrastructure resilience, and informing policy evaluation. In this work, we present a harmonized geospatial dataset for the electric distribution networks in the US Northeast, covering Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont. The dataset integrates technical, spatial, and topological data extracted from utility hosting capacity maps (public GIS layers reporting feeder-level estimates of distributed energy resources) and processed using a reproducible pipeline. Our network comprises 3,884,698 line segments, achieving a population coverage of 72.46% and geographic coverage of 84.96%. By bridging complex network theory with spatial infrastructure mapping, this dataset enables a multidimensional assessment of electric grid performance, sustainability, and equity. It allows researchers and policymakers to explore the links between urban and economic development patterns, network morphology, and energy outcomes.

Identifiers

PMID41419743
PMCPMC12865016

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.