MétaCan
Menu
Back to cohort
Record W2068560008 · doi:10.1021/jf035180l

Speciation of Arsenic in Different Types of Nuts by Ion Chromatography−Inductively Coupled Plasma Mass Spectrometry

2004· article· en· W2068560008 on OpenAlexfundno aff
Sasi S. Kannamkumarath, Kazimierz Wróbel, Katarzyna Wróbel, Joseph A. Caruso

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNational Institutes of HealthUniversity of British ColumbiaUniversity of Cincinnati
KeywordsArsenicChemistryInductively coupled plasma mass spectrometryChromatographyInductively coupled plasmaChloroformIon chromatographyMass spectrometryResidue (chemistry)Elemental analysisEnvironmental chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

In this work the quantitative determination and analytical speciation of arsenic were undertaken in different types of nuts, randomly purchased from local markets. The hardness of the whole nuts and high lipid content made the preparation of this material difficult for analysis. The lack of sample homogeneity caused irreproducible results. To improve the precision of analysis, arsenic was determined separately in nut oil and in the defatted sample. The lipids were extracted from the ground sample with the two portions of a mixture of chloroform and methanol (2:1). The defatted material was dried and ground again, yielding a fine powder. The nut oil was obtained by combining the two organic extracts and by evaporating the solvents. The two nut fractions were microwave digested, and total arsenic was determined by inductively coupled plasma mass spectrometry (ICP-MS). The results obtained for oils from different types of nuts showed element concentration in the range 2.9-16.9 ng g(-)(1). Lower levels of arsenic were found in defatted material (<0.1 ng g(-)(1) with the exception of Brazil nuts purchased with and without shells, 3.0 and 2.8 ng g(-)(1) respectively). For speciation analysis of arsenic in nut oils, elemental species were extracted from 2 g of oil with 12 mL of chloroform/methanol (2:1) and 8 mL of deionized water. The aqueous layer, containing polar arsenic species, was evaporated and the residue dissolved and analyzed by ion chromatography-ICP-MS. The anion exchange chromatography enabled separation of As(III), dimethylarsinic acid (DMAs(V)), monomethylarsonic acid (MMAs(V)), and As(V) within 8 min. Several types of nuts were analyzed, including walnuts, Brazil nuts, almonds, cashews, pine nuts, peanuts, pistachio nuts, and sunflower seeds. The recovery for the speciation procedure was in the range 72.7-90.6%. The primary species found in the oil extracts were As(III) and As(V). The arsenic concentration levels in these two species were 0.7-12.7 and 0.5-4.3 ng g(-)(1), respectively. The contribution of As in DMAs(V) ranged from 0.1 +/- 0.1 ng g(-)(1) in walnuts to 1.3 +/- 0.3 ng g(-)(1) in pine nuts. MMAs(V) was not detected in almonds, peanuts, pine nuts, sunflower seeds, or walnuts, and the highest concentration was found in pistachio nuts (0.5 +/- 0.2 ng g(-)(1)).

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.199

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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

Citations31
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicArsenic contamination and mitigationFrench-language works237,207