Evidence map›Paper›PMID 34347840›Full record

ArticlePloS one2021

Feature extraction and machine learning techniques for identifying historic urban environmental hazards: New methods to locate lost fossil fuel infrastructure in US cities.

Jonathan Tollefson, Scott Frickel, Maria I Restrepo

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Jonathan TollefsonDepartment of Sociology, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0002-1392-5841
Scott FrickelDepartment of Sociology, Brown University, Providence, Rhode Island, United States of America.
Maria I RestrepoCenter for Computation and Visualization, Brown University, Providence, Rhode Island, United States of America.

Funding

Vapor Pressures and Thermodynamic Properties of Complex Organic MixturesP42ES013660 · NIEHS · BROWN UNIVERSITY · PI BOEKELHEIDE, KIM, HURT, ROBERT H. · 2005 to 2020
$37.7M
NIEHS NIH HHS P42 ES013660
6 · The paper itself

Abstract

U.S. cities contain unknown numbers of undocumented "manufactured gas" sites, legacies of an industry that dominated energy production during the late-19th and early-20th centuries. While many of these unidentified sites likely contain significant levels of highly toxic and biologically persistent contamination, locating them remains a significant challenge. We propose a new method to identify manufactured gas production, storage, and distribution infrastructure in bulk by applying feature extraction and machine learning techniques to digitized historic Sanborn fire insurance maps. Our approach, which relies on a two-part neural network to classify candidate map regions, increases the rate of site identification 20-fold compared to unaided visual coding.

Indexed as

Machine LearningNeural Networks, ComputerCitiesEnvironmental MonitoringFiresFossil FuelsHumansIndustryUnited StatesUrban RenewalFossil Fuels

Identifiers

PMID34347840
PMCPMC8336811

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.