Cited by 201Regulation and Compliance StudiesArtificial Intelligence in LawData Mining and Machine Learning Applications

The DOI matches its Crossref record; 16 of the 17 references it cites were found in a registry or an index.

Machine learning for environmental monitoring

Hino, M., Benami, E., Brooks, N.·2018·Nature Sustainability

Overview

Integrity signals

Registry

Crossref · 10.1038/s41893-018-0142-9

Cites

16 of 16 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 1

  1. Zliobaite, I. Fairness-aware machine learning: a perspective. Preprint at https://arxiv.org/abs/1708.00754 (2017). · arXiv

Cited by

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Metadata

Authors
Hino, M., Benami, E., & Brooks, N.
Affiliations
Stanford University (US)
Corresponding author
Benami, E.
Venue
Nature Sustainability
Published
2018-10-01
Volume
1
Issue
10
Pages
583-588
ISSN
2398-9629 (ISSN-L)
OpenAlex
W2894463230
Cited by
201
References
17
Citations by year
2026: 27 · 2025: 55 · 2024: 41 · 2023: 22 · 2022: 19 · 2021: 16 · 2020: 8 · 2019: 11 · 2018: 1
FWCI
15.04
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Sustainability (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Public Administration › Regulation and Compliance Studies
  • Social Sciences › Law › Artificial Intelligence in Law
  • Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
Keywords
environmental law enforcement, Clean Water Act, resource allocation, gaming the system, regulatory compliance, environmental monitoring, big data, predictive analytics, Environmental Protection Agency

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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