MétaCan
Menu
Back to cohort
Record W2514481205 · doi:10.1080/1028415x.2016.1218191

The use of magnetic resonance spectroscopy for assessing the effect of diet on cognition

2016· review· en· W2514481205 on OpenAlexaff
Claire J. Scavuzzo, Christopher J. Moulton, Ryan J. Larsen

Bibliographic record

VenueNutritional Neuroscience · 2016
Typereview
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCognitionNeurotransmitterMagnetic resonance imagingPsychologyNeuroscienceMedicineCentral nervous system

Abstract

fetched live from OpenAlex

Magnetic resonance spectroscopy (MRS) is an important tool for studying the effects of nutrition on brain health. MRS can be used to measure the concentrations of metabolites which are related to cognitive performance and sensitive to diet. These measurements can provide information about metabolic efficiency, plasma membrane stability, antioxidant status, and neurotransmitter availability. MRS can therefore be used to elucidate the biochemical mechanisms by which diet influences cognition, and to characterize the effects of nutritional interventions targeted to improve cognition.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.098
GPT teacher head0.430
Teacher spread0.332 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations35
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueNutritional NeuroscienceSame topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207