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Record W4406038463 · doi:10.5376/be.2024.14.0026

Tea Oil and Their Role in Human Health: A Meta-Analysis

2024· article· en· W4406038463 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBiological Evidence · 2024
Typearticle
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisHuman healthPsychologyEnvironmental healthMedicineInternal medicine

Abstract

fetched live from OpenAlex

The primary goal of this study is to evaluate the health benefits of tea oil, focusing on its potential therapeutic effects and mechanisms of action in human health. The analysis revealed several key findings. Tea oil, rich in unsaturated fatty acids and bioactive compounds such as catechins and tea polyphenols, exhibits significant antioxidant, anti-inflammatory, and lipid-lowering properties. Studies have shown that tea oil can improve glucose and lipid levels, and modulate gut microbiota in diabetic models. Additionally, tea oil has demonstrated potential neuroprotective effects through its anti-inflammatory and immunomodulatory actions. Clinical trials and observational studies suggest that regular consumption of tea oil may reduce the risk of cardiovascular diseases and improve metabolic health. The findings of this study suggest that tea oil holds considerable promise as a natural therapeutic agent for various health conditions, including cardiovascular diseases, diabetes, and neuroinflammation. Further high-quality clinical trials are needed to substantiate these benefits and elucidate the underlying mechanisms.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.238
GPT teacher head0.398
Teacher spread0.160 · 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