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Record W2048725980 · doi:10.1155/2013/429847

An Evaluation of Interindividual Responses to the Orally Administered Neurotransmitter <b><i>β</i></b>-Alanine

2013· article· en· W2048725980 on OpenAlexafffund
Sarah MacPhee, Ian N. Weaver, Donald F. Weaver

Bibliographic record

VenueJournal of Amino Acids · 2013
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsNeurotransmitterMedicineAlaninePharmacologyDosingInternal medicineLimitingPhysiologyEndocrinologyCentral nervous systemAmino acidBiologyBiochemistry

Abstract

fetched live from OpenAlex

Previously, we have identified β -alanine as a potential endogenous anticonvulsant molecule. β -Alanine occurs within the human central nervous system and has been identified as both an inhibitory neuromodulator and neurotransmitter that is bioavailable to brain after oral administration. During preliminary compounding trials to ascertain dosing strategies for β -alanine, we noted pronounced differences in the side effect profile experienced by individuals of Asian and Caucasian descent. To investigate whether ethnicity affects β -alanine-induced side effects, we administered 3 g of β -alanine in 200 mL of fruit drink to ten people of each ethnic background and observed them for 30 minutes. Data collected included basic physical statistics (height, age, and weight) and descriptions of all side effects, as reported by participants. We found that participants of Asian descent experienced paraesthesia, but significantly different in time of onset, intensity, and anatomical localization, as compared to the effects experienced by Caucasian participants. Since β -alanine is an endogenous neurotransmitter substance within human brain, these side effect differences were unexpected.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.356
Teacher spread0.302 · 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 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

Citations17
Published2013
Admission routes2
Has abstractyes

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