Evidence map›Paper›PMID 37782376›Full record

ArticleEnvironmental monitoring and assessment2023

Trace metal content prediction along an AMD (acid mine drainage)-contaminated stream draining a coal mine using VNIR-SWIR spectroscopy.

Jamie-Leigh Robin Abrahams, Emmanuel John M Carranza

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2023. 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
0.3field-weighted citation impact, top 34% of its field
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, 2 citations in OpenAlex.

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

2 authors at 1 institution in 2 countries.

Jamie-Leigh Robin AbrahamsDepartment of Geology, Faculty of Natural and Agricultural Sciences, University of the Free State, 205 Nelson Mandela Drive, Park West, Bloemfontein, 9301, South Africa. jrobinabrahams@gmail.com.ORCID https://orcid.org/0000-0002-6575-1302
Emmanuel John M CarranzaDepartment of Geology, Faculty of Natural and Agricultural Sciences, University of the Free State, 205 Nelson Mandela Drive, Park West, Bloemfontein, 9301, South Africa.ORCID https://orcid.org/0000-0003-1765-0352
University of the Free State · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current study investigated the use of VNIR-SWIR (visible/near infrared to short-wavelength infrared: 400-2500 nm) spectroscopy for predicting trace metals in overbank sediments collected in the study site. Here, we (i) derived spectral absorption feature parameters (SAFPs) from measured ground spectra for correlation with trace metal (Pb, Cd, As, and Cu) contents in overbank sediments, (ii) built univariate regression models to predict trace metal concentrations using the SAFPs, and (iii) evaluated the predictive capacities of the regression models. The derived SAFPs associated with goethite in overbank sediments were Depth433

Indexed as

CadmiumTrace ElementsCoalEnvironmental MonitoringIron CompoundsKaolinLeadMineralsRiversSpectrum AnalysisCadmiumCoalgoethiteIron CompoundsKaolinLeadMineralsTrace ElementsFloodplain sedimentsHeavy metalPredictive modelingReflectance spectroscopyRemote sensing

Identifiers

PMID37782376
PMCPMC10545582
OpenAlexW4387241492

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.