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Record W4404766472 · doi:10.53555/sfs.v10i2.3197

Evaluating Seasonal Dynamics of Traditional Drinking Water Sources in Pithoragarh: A Physicochemical and Microbiological Perspective

2023· article· en· W4404766472 on OpenAlexvenueno aff
Shailu Garkoti

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Environmental scienceDynamics (music)PsychologyMathematics

Abstract

fetched live from OpenAlex

Water is the most widely distributed and abundant substance in nature, but only 3% is fit for human consumption.This study deals with the water quality analysis of the traditional water sources in the Pithoragarh city of Uttarakhand.These water sources are considered sacred traditional sources of drinking water in the Kumaun region.In the present study, samples were taken from 10 different sites and the physicochemical parameters analyzed, isolation, identification, and characteristics of bacteria with the antibiotic's sensitivity test were tested.The water pH ranges from 6.2 to 7.9, with temperatures of 8-18°C (water) and 10-21°C (air).Total dissolved solids were 114-498 mg/L, dissolved oxygen 5.8-7.4mg/L, carbon dioxide 0.4-2.8mg/L, alkalinity 56-202 mg/L, biochemical oxygen demand 1-2.9 mg/L, and electrical conductivity 309-798 μS/cm.ANOVA showed low significance (P<0.05) between water and air temperatures, but highly significant differences (P<0.001) for water temperature with TDS, CO₂, DO, BOD, alkalinity, and EC.Bacteria such as E. coli, Salmonella, Shigella, Campylobacter, and Clostridium were isolated on selective agar, but Yersinia showed no growth across all months and sites.Biochemical tests revealed site-specific bacterial presence, with all five bacteria positive in May and September at site 1 (SD) and varying positive results in summer months across other sites.Negative results were frequent in winter and early spring.The study revealed distinct antibiotic resistance patterns across bacterial species.E. coli, Salmonella, Shigella, and Campylobacter showed 50-90% resistance to tested antibiotics, with limited susceptibility.Clostridium exhibited the highest resistance, with 90% resistance to Metronidazole and 75% to Vancomycin.This study highlights the urgent need to protect traditional drinking water sources in Pithoragarh by addressing bacterial contamination and antibiotic resistance, guiding essential public health interventions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.266
GPT teacher head0.341
Teacher spread0.076 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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