MétaCan
Menu
Back to cohort
Record W4210352912

Bitter brain : Hypoglycemia and the pathology of neurodegeneration and dementia

2021· article· en· W4210352912 on OpenAlexaff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsTrent University
Fundersnot available
KeywordsNeurodegenerationHypoglycemiaDementiaNeuroscienceHippocampusMedicineHippocampal formationPopulationCognitive declineInternal medicineEndocrinologyDiabetes mellitusPsychologyDisease
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Glucose poses the predominant energy source of the brain and its continuous uptake is vital for optimal brain function. Neurons metabolize glucose to generate adenosine triphosphate via glycolysis and the tricarboxylic acid cycle, whereas astrocytes utilize glucose both as an energy source and to generate glutamine - a neurotransmitter precursor- for neurons [Brekke et al., 2015]. Here, we prospectively examine the relationship between chronic hypoglycemia and the associated links between neurodegeneration and dementia. It is proposed that severe episodes or chronic hypoglycemia will induce an increased risk of dementia. METHODS: A complex and specific literature search was conducted across various scientific, international databases for English, peer-reviewed articles and reviews published in the last two decades using the following terms: diabetes, insulin, glucose metabolism, hypoglycemia, and Alzheimer's disease (AD). Case reports were excluded. The main objectives were predominantly focused on animal- or human-based studies. RESULTS: When blood glucose levels are

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.357

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)0.0000.000

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 head0.019
GPT teacher head0.202
Teacher spread0.183 · 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 teacher head, 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueLancaster EPrints (Lancaster University)Same topicNeurological Disorders and TreatmentsFrench-language works237,207