Evidence map›Paper›PMID 31193115›Full record

ArticleMethodsX2019

Protocol for the estimation of drinking water quality index (DWQI) in water resources: Artificial neural network (ANFIS) and Arc-Gis.

Majid RadFard, Mozhgan Seif, Amir Hossein Ghazizadeh Hashemi, Ahmad Zarei, Mohammad Hossein Saghi, Naseh Shalyari, Roya Morovati, Zoha Heidarinejad, Mohammad Reza Samaei

Abstract read
In one paragraph

Article in MethodsX, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

9 authors.

Majid RadFardDepartment of Environmental Health Engineering, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Mozhgan SeifDepartment of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Amir Hossein Ghazizadeh HashemiShahid Beheshti University of Medical Sciences, Tehran, Iran.
Ahmad ZareiDepartment of Environmental Health Engineering, Faculty of Health, Gonabad University of Medical Sciences, Gonabad, Iran.
Mohammad Hossein SaghiDepartment of Environmental Health Engineering, School of Public Health, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Naseh ShalyariDepartment of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Roya MorovatiDepartment of Environmental Health Engineering, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Zoha HeidarinejadFood Health Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
Mohammad Reza SamaeiDepartment of Environmental Health Engineering, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drinking water sources may be polluted by various pollutants depending on geological conditions and agricultural, industrial, and other human activities. Ensuring the safety of drinking water is, therefore, of a great importance. The purpose of this study was to assess the quality of drinking groundwater in Bardaskan villages and to determine the water quality index. Water samples were taken from 30 villages and eighteen parameters including calcium hardness (CaH), total hardness (TH), turbidity, pH, temperature, total dissolved solids (TDS), electrical conductivity (EC), alkalinity (ALK), magnesium (Mg

Indexed as

Bardaskan villagesDrinking waterEstimation a water quality index in Bardaskan cityIranWQI

Identifiers

PMID31193115
PMCPMC6517571

What OpenQuestion holds

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LicenceCC BY
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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.