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Record W2234593635 · doi:10.5539/sar.v5n1p49

Some Evidences on Effect of Intake Aguamiel (Agave sap)

2016· article· en· W2234593635 on OpenAlexvenueno aff
Armando Carrillo‐López, Héctor Silos‐Espino, S. Flores-Benitez, Edward Alexander Espinoza-Sánchez, J. R. Ornelas-Tavares, L. Flores-Chávez, Clara Lourdes Tovar-Robles, J. Méndez-Gallegos, D. Rössel-Kipping

Bibliographic record

VenueSustainable Agriculture Research · 2016
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAgaveWhite blood cellPhysiologyPlateletFerritinPopulationCholesterolTransferrinAnimal scienceBiologyEndocrinologyInternal medicineMedicineImmunologyBotany

Abstract

fetched live from OpenAlex

Honeywater or aguamiel (Agave sap) has been consumed by Mexican population since pre-columbian times. Although, it has been claimed by folk belief that aguamiel possesses some medicinal properties, scientific studies on its effect on human health have not been well documented. The behavior of blood components in nine volunteers (two young males, three adult females and four adult males) after aguamiel consumption (250 mL every three days during a period of 35 days) was analyzed. It was found that, serum red blood cell count, serum white blood cell count, platelet count, minerals (Zn, Mg and Fe) and iron-related proteins (ferritin and transferrin) levels were not negatively affected because of all of these blood indicators ranged within normal reference values. However, this study showed that aguamiel presented a specific functional effect since hypercholesterolemic adult males showed normal levels of serum total cholesterol after aguamiel consumption, whereas total cholesterol levels were kept in normal ranges after aguamiel consumption for normocholesterolemic subjects. Furthermore, aguamiel consumption did not cause hyperglycemia in any of the tested groups.

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)0.002
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 score0.223
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.344
Teacher spread0.322 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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