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Record W2607801332 · doi:10.1038/s41598-017-01470-4

Omega-3 Long-Chain Polyunsaturated Fatty Acid Content and Oxidation State of Fish Oil Supplements in New Zealand

2017· article· en· W2607801332 on OpenAlexaff
Gerard Bannenberg, Craig Mallon, Holly Danielle Edwards, Derek Yeadon, Kevin L. Yan, H.L. Johnson, Adam Ismail

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsNutrasource
FundersDSM Nutritional ProductsSouth Dakota Governor's Office of Economic Development
KeywordsEicosapentaenoic acidDocosahexaenoic acidFish oilFish <Actinopterygii>Polyunsaturated fatty acidPeroxide valueFood scienceChemistryFatty acidBusinessFisheryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Forty-seven fish oil products available on the New Zealand market were analyzed for eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content, as well as for oxidative status in a collaborative effort by several analytical laboratories. Of the tested products, 72%, 86% and 77% complied with voluntary industry-set maximum limits on Peroxide Value (PV), para -Anisidine Value (p-AV), and TOTOX, respectively. 91% of the products complied with EPA/DHA content claims. All fish oils complied with a p-AV limit of 30, 98% with a PV limit of 10 meq O 2 /kg, and 96% with a calculated TOTOX value of 50, which are less stringent limits used by the European and British Pharmacopeia and the Australian authorities. The results are in stark contrast to the very low percentage of fish oil products reported to be in compliance with primary oxidation limits and EPA/DHA content by a recently published assessment of fish oil supplements in New Zealand. Possible reasons for this discrepancy are evaluated and discussed.

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)0.001
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 score0.089
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.047
GPT teacher head0.322
Teacher spread0.276 · 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

Citations83
Published2017
Admission routes1
Has abstractyes

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