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Record W2127571373 · doi:10.5296/jbls.v4i1.3084

Heavy Metal Pollution in the Receiving Environment of the University of Dar Es Salaam Waste Stabilization Ponds

2013· article· en· W2127571373 on OpenAlexaff
Adrehem J. Nziku, Lucy Namkinga

Bibliographic record

VenueJournal of Biology and Life Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsClarias gariepinusOreochromisGillCadmiumBioaccumulationMercury (programming language)Environmental chemistryArsenicChemistryAnimal scienceFisheryVeterinary medicineBiologyFish <Actinopterygii>Catfish

Abstract

fetched live from OpenAlex

The aim of this study was to examine the availability, concentration levels and bioaccumulation of heavy metals namely; Mercury (Hg), Cadmium (Cd), Lead (Pb), Zinc (Zn) and Molybdenum (Mo) in the waste Stabilization Ponds of the University of Dar es Salaam. A total of 135 samples were analyzed, out of which 27 were samples of water, 27 of sediments and 81 samples of fish tissues. Two types of fishes were used namely; Oreochromis niloticus and Clarias gariepinus. Heavy metal concentration varied significantly between water, sediment, fish species and tissues. Hg, Cd, Zn and Mo concentrations in water and sediment were within WHO safe limits. However, Pb in water and Cd, Pb and Zn concentrations in sediments were found to be above WHO standards (p&lt;0.05). Concentration levels for Cd, Pb and Zn were above acceptable levels in Oreochromis niloticus while Hg was found to be within safe limits in both fish species (p&lt;0.05). Molybdenum was found to be below the detection limits in Oreochromis niloticus. While Cd was not detected, Pb, Zn and Mo were found highly accumulated in Clarias gariepinus (p&lt;0.05). Oreochromis niloticus accumulated metals in the increasing order from dorsal muscles &lt; gills &lt; liver while Clarias gariepinus accumulated metals in the decreasing order from dorsal muscle &lt; gills &lt; liver.Public awareness on the dangers to which fish consumers from the site are exposed is highly suggested and purposeful mitigation measures of stopping all fishing activities in these sites is needed, also animal feeding around the ponds should be forbidden.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.207
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2013
Admission routes1
Has abstractyes

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