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Record W2720599164 · doi:10.6000/1927-5129.2017.13.60

Assessment of Drinking Water Quality Status and its Impact on Health in Tandojam City

2017· article· en· W2720599164 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceWater qualityWater sourceGroundwaterWaterborne diseasesEnvironmental healthToxicologyWater resource managementEnvironmental engineeringEcologyBiologyMedicine

Abstract

fetched live from OpenAlex

Unsafe drinking water is one of the major concerns in developing countries. The southern Sindh is province of Pakistan that adjoins the Arabian Sea coast where the drinking water quality is deteriorating due to unrefined urban waste and excessive use of agro-chemicals. Present study aimed to assess the quality of ground water source and to compare it with WHO standards. Water borne diseases associated with drinking it in the vicinity Tandojam city were identified. Water from ground water source was sampled at selected locations in the study area. The samples were collected mostly from pumped waters. The samples were analyzed for physico-chemical properties in order to identify the quality problems and suggest safe source for drinking purpose. Findings revealed that the ground water quality in Muzaffrabad colony is deteriorating. The situation was much worse in Muzaffrabad colony, Jam Ghar and Mir colony with high TDS and salty taste, respectively at few sampling locations. In addition, laboratory analysis of the water quality parameters revealed the detail of variation in the groundwater. TDS, hardness, sodium (Na), chloride (Cl) and magnesium (Mg) etc. were considerably beyond the WHO permissible limits. The poor quality of the water has created different waterborne diseases like cholera, diarrhea etc. Moreover, the samples of SAU Colony and Amar Town showed that the water quality of these areas was within acceptable limits according to WHO standards and was suitable for the purpose of drinking.

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.

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)0.006
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 score0.062
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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 head0.066
GPT teacher head0.408
Teacher spread0.342 · 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