Evidence map›Paper›PMID 37743952›Full record

ArticleACS environmental Au2023

Development of a Soft Sensor Using Machine Learning Algorithms for Predicting the Water Quality of an Onsite Wastewater Treatment System.

Hsiang-Yang Shyu, Cynthia J Castro, Robert A Bair, Qing Lu, Daniel H Yeh

Abstract read
In one paragraph

Article in ACS environmental Au, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Water quality monitoring using hybrid physical-soft sensors for river digital twins: a comprehensive review.Water science and technology : a journal of the International Association on Water Pollution Research · 2025
    Review
  7. Review
  8. Review
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

5 authors.

Hsiang-Yang ShyuCivil & Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, Florida 33620, United States.ORCID https://orcid.org/0000-0001-9428-3678
Cynthia J CastroCivil & Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, Florida 33620, United States.ORCID https://orcid.org/0000-0001-6645-7319
Robert A BairCivil & Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, Florida 33620, United States.
Qing LuCivil & Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, Florida 33620, United States.ORCID https://orcid.org/0000-0002-9120-9218
Daniel H YehCivil & Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, Florida 33620, United States.ORCID https://orcid.org/0000-0002-8365-9657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing advanced onsite wastewater treatment systems (OWTS) requires accurate and consistent water quality monitoring to evaluate treatment efficiency and ensure regulatory compliance. However, off-line parameters such as chemical oxygen demand (COD), total suspended solids (TSS), and

Identifiers

PMID37743952
PMCPMC10515708

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.