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Record W4401542392 · doi:10.1111/ijfs.17423

Impact of the incorporation of the edible seaweeds <i>Saccharina latissima</i> and <i>Alaria esculenta</i> on the physicochemical, functional and sensory properties of yoghurt

2024· article· en· W4401542392 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsUniversité Laval
FundersMitacsUniversité Laval
KeywordsFood scienceSyneresisChemistryOrganolepticBotanyBiology

Abstract

fetched live from OpenAlex

Abstract The impact of the addition of seaweed to yoghurt was evaluated on its physicochemical, functional and sensory properties. Two different species of brown macroalgae, Saccharina latissima (blanched or not) and Alaria esculenta, were added in four different concentrations (0.25%, 0.50%, 0.75% and 1%) and in two different forms (flakes and powder). The titratable acidity of all yoghurt samples formulated with blanched Saccharina was similar to the control. However, formulations with blanched Saccharina exhibited higher syneresis than the control. Most yoghurt samples containing Alaria at higher concentrations exhibited a lower firmness than the control. Seaweed addition had a significant impact on the colour of yoghurt samples. Quantitative descriptive analysis and hedonic evaluation performed by a trained panel showed that changes in physicochemical properties influenced the organoleptic characteristics of yoghurt samples. Yoghurt samples formulated with 0.25% S. latissima and 0.50% A. esculenta in flakes were selected as the most promising formulations.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.242
Teacher spread0.212 · 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