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Record W4309550195 · doi:10.1111/ijfs.16204

Does it burn? The effect of guar gum addition on ginger beer's sensory properties

2022· article· en· W4309550195 on OpenAlexaff
Sophie Knowles, Mackenzie Gorman, Matthew B. McSweeney

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2022
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicGinger and Zingiberaceae research
Canadian institutionsAcadia University
Fundersnot available
KeywordsGuar gumFood scienceFlavourSweetnessMouthfeelGuarChemistryXanthan gumTasteMaterials science

Abstract

fetched live from OpenAlex

Summary Consumer demand for ginger beer has grown within the last few years due to health benefits associated with ginger consumption identified in recent studies and its low‐calorie content. However, non‐alcoholic ginger beer, like other non‐alcoholic beverages, does not possess the same mouthfeel as its alcoholic counterparts. As such, the aim of this study was to evaluate how the addition of guar gum impacted the sensory perception, spiciness, and consumer acceptability of non‐alcoholic ginger beer. Two different formulations of ginger beer were created, one without the addition of guar gum (control) and the other with 1.9 g/L guar gum added. Samples, along with carbonated water, were presented in pairs with a 20‐s wait and no‐rinse in between to observe sensitisation and desensitisation. The participants ( n = 103) evaluated each sample for spiciness, burning or stinging sensation, along with bitterness, sweetness, sourness, overall flavour intensity, liking of flavour and mouthfeel, and overall liking. The addition of guar gum significantly impacted the perception of spiciness, burning, and stinging sensation in addition to the overall flavour intensity. The guar gum addition also negatively impacted the acceptability of the ginger beer.

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)0.001
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 score0.065
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.424
Teacher spread0.351 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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