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Record W1966295347 · doi:10.1080/10934529.2012.707542

Environmental contamination of ready meals by polychlorinated biphenyls (PCBs)

2012· article· en· W1966295347 on OpenAlexaff
Adeola A. Adenugba, Dena W. McMartin, Angus J. Beck

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of Regina
FundersImperial College London
KeywordsContaminationEnvironmental chemistryEnvironmental sciencePolychlorinated biphenylChemistryBiologyEcology

Abstract

fetched live from OpenAlex

The level of polychlorinated biphenyls (PCBs) contamination in ready meals was investigated to determine exposure compared to other foodstuffs. Chilled ready meals from nine categories (ambient, Chinese, Indian, Traditional UK, Italian, American Tex-Mex, Vegetarian and Organic), and three samples within each category were Soxhlet extracted in triplicate with hexane for 24 h, followed by a clean-up on deactivated silica gel. The cleaned extracts were concentrated to 1 ml under N(2) gas and analyzed on gas chromatography mass spectrometry (GC-MS) for 7 target PCBs (congeners 28, 52, 101, 118, 153, 138, and 180). Individual congener concentrations ranged from non-detectable to 0.40 ng g(-1) (wet weight). The cumulative concentration of all congeners (ΣPCBs) ranged between 0.20 and 1.00 ng g(-1) (wet weight). These values translate into exposure levels of less than 1 μg kg(-1)day(-1) for reference men and women of 70 and 57 kg, respectively. This preliminary study demonstrates that ready meals, like many other foods, are contaminated by PCBs and may represent an important route of human exposure given contemporary changes in consumer food choice. Even though low levels of contamination were observed, long-term exposure for population groups consuming a high volume of ready meals may have cause for concern regarding chronic health risks.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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Same venueJournal of Environmental Science and Health Part ASame topicToxic Organic Pollutants ImpactFrench-language works237,207