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Record W2086543414 · doi:10.1080/09637480802389094

Chemical composition and glycemic index of three varieties of Omani dates

2008· article· en· W2086543414 on OpenAlexfundno aff
Amanat Ali, Yusra S.M. Al-Kindi, Fahad Al‐Said

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDate Palm Research Studies
Canadian institutionsnot available
FundersSultan Qaboos UniversityUniversity of Toronto
KeywordsGlycemic indexIndex (typography)Composition (language)GlycemicBiologyDiabetes mellitusEndocrinologyComputer scienceWorld Wide WebArt

Abstract

fetched live from OpenAlex

The present study evaluated the nutritional quality and glycemic index of three sun-dried date varieties (Khalas, Khsab and Fardh) grown in Oman. Significant (P<0.05) differences were observed in the proximate chemical composition, dietary fiber contents, various sugar fractions and energy value of these dates. The moisture, ash, crude protein, total fat, and nitrogen-free extract values ranged between 18.77 and 23.71 g/100 g date flesh, 1.12 and 1.55 g/100 g date flesh, 1.28 and 1.89 g/100 g date flesh, 1.14 and 2.37 g/100 g date flesh, and 68.53 and 75.37 g/100 g date flesh, respectively. The dietary fiber and total sugar contents ranged between 8.83 and 13.11 g/100 g and between 52.17 and 59.96 g/100 g, respectively. The glycemic index (GI) of different varieties of dates collected from various regions of Oman ranged between 47.6 and 57.7. Overall no significant (P<0.05) differences were observed in the GI values of different varieties of dates. The regional effects on the GI values of dates were also non-significant (P>0.05). An inverse correlation (r(2)) was observed between the fructose fraction and the GI value of dates.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.044
GPT teacher head0.269
Teacher spread0.225 · 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 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

Citations64
Published2008
Admission routes1
Has abstractyes

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Same venueInternational Journal of Food Sciences and NutritionSame topicDate Palm Research StudiesFrench-language works237,207