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Record W4321376412 · doi:10.53623/tasp.v3i1.177

Assessment of the Physiochemical Characteristics of Water Samples from Vicinity Area of Wadafiae Landfill, Khartoum North, Sudan

2023· article· en· W4321376412 on OpenAlexaboutno aff
Omer Abbass Elamin, Abdelelah Mohamed Elhassan, Abdelgadir Elfadil Abdelgadir, Mariam Hamdan Ahmed

Bibliographic record

VenueTropical Aquatic and Soil Pollution · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceMunicipal solid wasteUrbanizationGroundwaterPopulationPollutionWater resource managementEnvironmental protectionEnvironmental engineeringGeographyWaste managementEnvironmental healthEcologyGeology

Abstract

fetched live from OpenAlex

The rapid increase in population, urbanization, industrialization, and changes in consumption patterns have given rise to many environmental problems, which mainly include air, land, and water pollution. In Khartoum North, Khartoum State, Sudan, there was a lack of a compatible solid waste management system. These resulted in a decline in environmental health, and the majority of the yards were turned into dumps (kusha). The current study focused on the effects of uncontrolled dumping of municipal solid waste on groundwater, as well as assessing the risk of physiochemical concentrations in the water around the dumpsite and comparing the differences between the dry and rainy seasons in water samples at Wadafiea Dumpsite, Khartoum North, Sudan. Water parameters such as TSS, Cl⁻, TDS, Ca, Mg, SAR, and Na exceeded the controlled 1 (1.333) and 2 (1.332) levels of water and were within the Sudanese Maximum Values, the bounds of Canadian Guideline Values, and WHO Values.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.228
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2023
Admission routes1
Has abstractyes

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