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Record W2999904763

Investigaciones actuales de bebidas energizantes y sus efectos en el consumidor

2019· dissertation· es· W2999904763 on OpenAlexaboutno aff
Mendoza Quispe, Nancy Beryl Janet

Bibliographic record

VenueUniversidad Nacional de Trujillo · 2019
Typedissertation
Languagees
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessPopularityEnvironmental healthAnxietyMedicineAdvertisingPolitical sciencePsychiatryLaw
DOInot available

Abstract

fetched live from OpenAlex

Currently, the use of energy drinks is daily and is increasing, the popularity that these products generate a rapid cure for exhaustion and the easy access to these products makes the consumer can easily acquire them, without knowing the adverse effects caused by these products. This research aims to know the current information on studies regarding energy drinks and the effect it produces on the consumer. At present there is no evidence of studies that recommend the use of energy drinks; However, there are studies and evidences of the harmful effect of some of its components used in the manufacture of these products, therefore, it is recommended that before consuming them, the nutritional information of the content and the effects that it causes in the body such as headache is reviewed. , diuresis, dehydration, arrhythmias, abdominal pain, vomiting, insomnia, anxiety, sweating and even dependence, among other effects. On the other hand, it is recommended to conduct more studies on the safety of these drinks, and duly inform the consumer. In Peru there is no legal system for the control of energy drinks for proper use, as they do in other developed countries: United Kingdom, Lithuania and Europe, prohibit the sale to minors, restrict their sale in events, prohibit advertising in media where minors have access, as well as countries such as Argentina, Uruguay, Mexico, Canada, France, Denmark, Sweden, laws have been enacted to regulate the sale of energy drinks as well as their components.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.312
Teacher spread0.298 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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