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Record W2612151698 · doi:10.6000/1927-5129.2017.13.34

Determination of Heavy Metals in the Different Samples of Table Salt

2017· article· en· W2612151698 on OpenAlexvenueno aff
Muhammad Aman Rizwan, Murtaza Haider, Abrar U. Hassan, Sakhawat Ali

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2017
Typearticle
Languageen
FieldChemistry
TopicHeavy Metals in Plants
Canadian institutionsnot available
Fundersnot available
KeywordsAtomic absorption spectroscopyCadmiumManganeseSalt (chemistry)ChemistryChromiumEnvironmental chemistryHeavy metalsTable (database)ContaminationCopperMetal

Abstract

fetched live from OpenAlex

Table salt is most widely used food additive around the globe. Any contamination to salt may lead to health hazards and ailments. In this study concentration of heavy metals were determined in different table salt sample. Twelve different salt sample were collected from various localities of Pakistan including all the four provinces. The concentration lead (Pb), Cadmium (Cd), Chromium (Cr), Iron (Fe), Manganese (Mn) and Copper (Cu) were determined by atomic absorption spectroscopy and compared it with Codex Alimentarius commission. The level of Pb, Cd, Cr, Fe, Mn and Cu were in the range of 0.1-2.96 mg/kg, 0.08-1.18 mg/kg,0.02-2.4 mg/kg, 2.5-16.7 mg/kg, 0.1-5.1 mg/kg, 0.6-3.1 mg/kg respectively. In most of the sample the level of toxic metal are within the permissible limits as prescribed by Codex Alimentarius Commission.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.063
GPT teacher head0.319
Teacher spread0.256 · 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 designBench or experimental
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

Citations7
Published2017
Admission routes1
Has abstractyes

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