MétaCan
Menu
Back to cohort

Antioxidant parameters and cognitive function according to FV consumption and combined GST genotype.

2015· paratext· en· W2399276768 on OpenAlexaboutno aff
Yuan Linhong, MA Wei-wei, Jinmeng Liu, Meng Liping, Liu Jixia, Shuang Li, Jing Han, Quanri Liu, Feng Lingli, Chao Wang, Rong Xiao

Bibliographic record

VenueFigshare · 2015
Typeparatext
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAntioxidantGenotypeCognitionFunction (biology)Consumption (sociology)BiologyBioinformaticsGeneticsBiochemistryGeneNeuroscienceSociology

Abstract

fetched live from OpenAlex

<p>General linear model used. Data are presented as the mean ± SE. For antioxidant biomarker data analysis, factors including age, sex, BMI, smoking and antioxidant supplement were adjusted. For cognitive function (MoCA score) data analysis, factors including age, sex, BMI, education, family history of AD, physical activity and participation in cognitive activity were adjusted. FV, fruit and vegetable; GSH-Px, glutathione peroxidase; GST, glutathione S-transferase; GR, glutathion reductase; CAT, catalase; SOD, superoxide dismutase; GSH, glutathione; T-AOC, total antioxidant capacity; MoCA, Montreal Cognitive Assessment. <i>P</i> value<0.05 was considered as significant.</p>a<p>: <i>P <sub>genotype</sub></i> = 0.036, <0.05. <i>P<sub>FV and genotype</sub></i> = 0.318, >0.05;</p>b<p>: <i>P<sub>FV</sub></i> = 0.384, <i>P <sub>genotype</sub></i> = 0.413; <i>P<sub>FV and genotype</sub></i> = 0.004, <0.01.</p><p>Antioxidant parameters and cognitive function according to FV consumption and combined GST genotype.</p>

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0140.008

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 head0.089
GPT teacher head0.333
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicNutrition, Health and Food BehaviorFrench-language works237,207