MétaCan
Menu
Back to cohort
Record W4366435716 · doi:10.37867/te140493

ANALYSIS OF WATER QUALITY THROUGH PHYSICO – CHEMICAL PARAMETERS OF THE REGION KHADIR BET, KACHCHH

2022· article· en· W4366435716 on OpenAlex
Ashmabanu Kazi, Harsh Patel, Archana Mankad

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTowards Excellence · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsImpact
Fundersnot available
KeywordsSodium adsorption ratioLivestockSodiumWater qualityEnvironmental scienceEnvironmental chemistryHydrology (agriculture)ChemistryGeologyAgronomyGeographyEcologyBiologyForestryGeotechnical engineering

Abstract

fetched live from OpenAlex

The present study was conducted to assess water quality using physico – chemical parameters. Water samples consumed by the livestock were collected from selected locations of Khadir bet, Kachchh region. The parameters analyzed include pH, EC, TDS, chloride, Ca+2 + Mg+2, Sodium, RSC (Residual sodium Carbonates), and SAR (Sodium Adsorption Ratio). Livestock lives in close proximity to humans, so the permissible limit of drinking water is the same in India. The results obtained in the analysis show that there were several parameters that were found to be beyond limits in the physico – chemical analysis. In the obtained result, it becomes clear that at some locations drinkable water used by the livestock is considerably polluted and unfit to be consumed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.293
Teacher spread0.241 · 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