MétaCan
Menu
Back to cohort
Record W2925665335 · doi:10.5539/jfr.v8n3p42

Product Development Considerations of Flaxseed Supplementation for the Aging Population: A Pilot Study

2019· article· en· W2925665335 on OpenAlexvenueno aff
Jenny Nguyen, Cheryl Rock, Virginia Gray, Maria Claver, Christine Costa

Bibliographic record

VenueJournal of Food Research · 2019
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsnot available
Fundersnot available
KeywordsWaistMedicinePalatabilityObesityPopulationGerontologyEnvironmental healthFood scienceInternal medicineBiology

Abstract

fetched live from OpenAlex

Obesity, cardiovascular disease, and vulnerability among older adults highlight a critical need for a careful consideration of effective and preventive dietary interventions. Consuming flaxseed, along with a well-balanced diet, has been shown to significantly improve weight, waist circumference, blood pressure, serum lipids, plasma glucose levels, and inflammatory biomarkers. Although flaxseed exhibits anti-inflammatory and antioxidant properties, little is known regarding its consumer acceptability among older adults. The objective of this study was to investigate the acceptability of a bagel with 23% flaxseed in individuals 50 years and older using a 9-point Hedonic rating scale, Paired Preference test, and Food Action (FACT) rating scale. There were no significant differences between the control and flaxseed bagel in sensory attributes and FACT ratings in 20 participants (69.0 ± 6.3 years old). Age was significantly associated with the overall acceptability of the flaxseed bagel (p = 0.004). Appearance, color, flavor, and texture were strongly correlated (p < 0.01) to overall acceptability in both bagels. Further exploration of consumer acceptance of flaxseed products among older adults is needed; clinical trials may also shed light on potential health impacts of regular flax consumption.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.224
GPT teacher head0.472
Teacher spread0.248 · 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 designNon-randomized trial
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Food ResearchSame topicPhytoestrogen effects and researchFrench-language works237,207