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Record W2762149882 · doi:10.24870/cjb.2017-a148

Analysis of ground water and soil samples from severely arsenic affected blocks of Murshidabad district

2017· article· en· W2762149882 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

VenueCanadian Journal of Biotechnology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Science and Fertilization
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterArsenicEnvironmental scienceArsenic contamination of groundwaterGeographyWater resource managementHydrology (agriculture)GeologyChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

Contamination of groundwater and soil by arsenic is a serious threat to existence of mankind on the globe. Arsenic contaminates soil and groundwater by natural biogeochemical cycles. However, due to anthropogenic activities like indiscriminant use of arsenic in disinfectants, weedicides, medicines and fertilizers, arsenic toxicity is a severe environmental issue, both at national and global level. U.S. Environmental Protection Agency and World Health Organization prescribed the permissible limit of arsenic in drinking water to be 10 g/l. Exposure to arsenic at higher levels over a considerable period of time leads to skin lesions and cancer, disorders of cardiovascular, respiratory, gastrointestinal, hepatic and renal systems. Murshidabad is one of the severely arsenic affected districts of West Bengal. We have analyzed soil and groundwater samples from some of the highly arsenic affected blocks of Murshidabad district. Both the soil and groundwater samples have an alkaline pH, a characteristic of the presence of arsenic in the tested samples. Unfortunately, the socio-economic conditions of these villages force the residents to use groundwater as the source of drinking water. Presence of considerably high amount of total dissolved solids in water samples make them further unfit for consumption. High amount of phosphate and iron present in some of the water samples takes a toll on the detoxification and excretory system of the body, if those water samples are consumed on a regular manner. Contamination of soil by the aforesaid contaminants results in biomagnification of these pollutants in the food chain. We could also isolate certain potentially arsenic resistant bacteria from the contaminated soil and water samples. At the next level we have surveyed an arsenic affected village to analyze the clinical manifestation of arsenic poisoning. In this village subjects developed rampant skin lesions throughout the body due to exposure to arsenic contaminated groundwater. Also, the disorders of various physiological systems could be observed in the subjects leading to death of the subject in extreme cases. Children as young as 13 years are also the victims of arsenic toxicity. Further research for bioremediation and inhibition of biomagnification of arsenic is the need of the hour to combat the menace of arsenic toxicity.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.962

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 head0.018
GPT teacher head0.200
Teacher spread0.182 · 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