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Record W2299796069 · doi:10.1177/1533317515628052

Hydrogen Proton Magnetic Resonance Spectroscopy in Multidomain Amnestic Mild Cognitive Impairment and Vascular Cognitive Impairment Without Dementia

2016· article· en· W2299796069 on OpenAlexfundno aff
Shuangqing Chen, Qing Cai, Yuying Shen, Xu Chuanxiao, Hua Zhou, Zhong Zhao

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeCanadian Stroke Network
KeywordsCreatineWhite matterDementiaInternal medicineCognitive impairmentPsychologyAudiologyCardiologyMagnetic resonance imagingNuclear magnetic resonanceMedicineChemistryNeuroscienceCognitionPhysicsRadiology

Abstract

fetched live from OpenAlex

To investigate the value of hydrogen proton magnet resonance spectroscopy ((1)H-MRS) in the differential diagnosis of multiple-domain amnestic mild cognitive impairment (M-aMCI) and vascular cognitive impairment with no dementia (VCIND); (1)H-MRS was performed in patients with M-aMCI and VCIND. The level was determined for N-acetylaspartate (NAA), glutamate (Glu), inositol (mI), choline (Cho), and creatine (Cr). Compared with the normal control group, the NAA-Cr ratio in all regions studied was significantly lower in the M-aMCI and VCIND groups. The Glu-Cr ratio in the posterior cingulate gyrus of the M-aMCI group was significantly lower than in the VCIND. The mI-Cr ratio in the frontal white matter of the VCIND was significantly higher than in the M-aMCI group. In the white matter adjacent to the lateral ventricles, the Cho-Cr ratio was significantly higher in the VCIND than the M-aMCI. Our results suggested (1)H-MRS is an effective method in the differential diagnosis of M-aMCI and VCIND.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.301
Teacher spread0.289 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Alzheimer s Disease & Other Dementias®Same topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207