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Mineral oil hydrocarbons in minimally processed nutraceutical oils

2022· preprint· en· W4296293241 on OpenAlexaff
Oladimeji Adewusi, Suzanne M. Budge, Christopher Barry, Jenna Sullivan Ritter

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMineral oilSaponificationChemistryPetroleumFood and drug administrationPetroleum productEnvironmental scienceEnvironmental chemistryFlame ionization detectorGas chromatographyPulp and paper industryChromatographyOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

The presence of unintended chemicals in food products and supplements may impact consumers’ health negatively. Mineral oil hydrocarbons (MOHs) in particular are gaining research attention and have been detected and quantified in food products and supplements in the past. The aim of this study was to analyze encapsulated, and bulk minimally processed marine oils for MOHs and to evaluate the probable sources of these compounds. Hydrocarbons in supplement oils were extracted via saponification and analyzed by gas chromatography with both flame ionization and mass spectral detection. While no mineral oil aromatic hydrocarbons (MOAH) were detected in any sample, the analysis revealed the presence of mineral oil saturated hydrocarbons (MOSH) in 9 out of 10 minimally processed encapsulated oils. The MOSH appeared on the chromatograms as an unresolved complex mixture (UCM) with concentrations ranging from 376 ± 49 to 3831 ± 414 mg kg-1. These values are well below the maximum allowable limits for MOH in encapsulated products set by the United States Food and Drug Administration. Therefore, all the tested products are compliant with the US regulations. Moreso, the bulk oil samples did not contain detectable levels of MOH. This study suggests that MOH accumulation in encapsulated products is likely due to the use of lubricants during encapsulation, rather than environmental sources such as oil spills since MOAH that are characteristic of weathered petroleum products were not identified in the UCM.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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
Published2022
Admission routes1
Has abstractyes

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