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Record W4210808658 · doi:10.1080/19440049.2021.2023765

Bisphenol S in individual and composite meat and meat products and implication for its sources

2022· article· en· W4210808658 on OpenAlexaffabout
Xu‐Liang Cao, Simon Ningsun Zhou, Svetlana Popović, Robert Dabeka

Bibliographic record

VenueFood Additives & Contaminants Part A · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsHealth Canada
Fundersnot available
KeywordsFood scienceRaw meatProcessed meatRed meatBisphenol SCooked meatFood productsMeat packing industryChemistryBisphenol A

Abstract

fetched live from OpenAlex

In this study, the occurrence of bisphenol S (BPS) in the meat and meat products from a recent Canadian Total Diet Study (TDS) was investigated in more detail. In addition to their composite samples, the individual raw meat and meat products were also analysed for BPS to investigate the variations of BPS levels and provide some information on the potential sources for BPS in meat. BPS was detected in all the 11 composite samples of different meat and meat products, with the highest level in roast beef (118.23 ng/g) and lowest in cured pork (0.14 ng/g) and cold cuts luncheon meats (0.18 ng/g). BPS was also detected in all the 84 individual raw meat and meat products, with the highest level of 257.61 ng/g in roast beef, followed by 190.41 ng/g in organ meats, 110.15 ng/g in beef steak, 27.91 ng/g in veal cutlets, 17.63 ng/g in wieners & sausages, and 15.27 ng/g in ground beef. However, significant variations of BPS levels were observed in the individual meat and meat product samples under the same category collected from different stores. This may indicate that packaging is unlikely the sources for BPS in meat otherwise BPS levels would have been more or less the same with the same type of packaging (Styrofoam and cling film) regardless where they were collected. Thus, sources other than food packaging, such as the contaminated feed and farming environment (e.g. grass) for animals (e.g. cow), may be possible and should be investigated in future studies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.508

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 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

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFood Additives & Contaminants Part ASame topicEffects and risks of endocrine disrupting chemicalsFrench-language works237,207