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Record W1537321255 · doi:10.1111/bpa.12221

Cerebral Amyloid Angiopathy, Subcortical White Matter Disease and Dementia: Literature Review and Study in <scp>OPTIMA</scp>

2014· review· en· W1537321255 on OpenAlexfundno aff
Margaret M. Esiri, Steven A. Chance, Catharine Joachim, Donald Warden, Aidan Smallwood, Carolyn Sloan, Sharon Christie, Gordon Wilcock, A. David Smith

Bibliographic record

VenueBrain Pathology · 2014
Typereview
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
FundersNIHR Oxford Biomedical Research CentreMedical Research CouncilChinese Academy of Agricultural SciencesAlzheimer Society
KeywordsCerebral amyloid angiopathyDementiaApolipoprotein EDiseaseIntracerebral hemorrhageNeuroimagingWhite matterPsychologyNeuroscienceMedicineAmyloid (mycology)PathologyInternal medicineMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Cerebral amyloid angiopathy (CAA) is of increasing clinical and research interest as the ability to detect it and its consequences by neuroimaging in living subjects has advanced. There is also increasing interest in understanding its possible role in the development of intracerebral hemorrhage, Alzheimer's disease (AD) and vascular dementia. In this article, the literature on this subject is reviewed and novel findings relating CAA to subcortical white matter damage in 224 subjects in the Oxford project to Investigate Memory and Ageing (OPTIMA) are reported. The relationship between CAA and subcortical tissue damage in the OPTIMA subjects was found to be critically dependent on ApoE genotype, there being a positive relationship between measures of CAA and subcortical small vessel disease in ApoEε4 carriers and a significant negative relationship in ApoEε2 carriers. These findings draw attention, as have many other studies, to the importance of ApoE genotype as a major risk factor not only for dementia but also for damage to blood vessels in the aging brain.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.009
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.324
Teacher spread0.305 · 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

Citations55
Published2014
Admission routes1
Has abstractyes

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