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Record W2615387318 · doi:10.1042/cs20160607

Clinical presentations and epidemiology of vascular dementia

2017· review· en· W2615387318 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Science · 2017
Typereview
Languageen
FieldMedicine
TopicCerebrovascular and genetic disorders
Canadian institutionsHealth Sciences CentreUniversity of Calgary
Fundersnot available
KeywordsNeuropathologyDementiaMedicineStroke (engine)Vascular dementiaDiseasePopulationEtiologyIntensive care medicineCardiologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Cerebrovascular and cardiovascular diseases cause vascular brain injury that can lead to vascular cognitive impairment (VCI). VCI is the second most common neuropathology of dementia and mild cognitive impairment (MCI), accounting for up to one-third of the population risk. It is frequently present along with other age-related pathologies such as Alzheimer's disease (AD). Multiple etiology dementia with both VCI and AD is the single most common cause of later life dementia. There are two main clinical syndromes of VCI: post-stroke VCI in which cognitive impairment is the immediate consequence of a recent stroke and VCI without recent stroke in which cognitive impairment is the result of covert vascular brain injury detected only on neuroimaging or neuropathology. VCI is a syndrome that can result from any cause of infarction, hemorrhage, large artery disease, cardioembolism, small vessel disease, or other cerebrovascular or cardiovascular diseases. Secondary prevention of further vascular brain injury may improve outcomes in VCI.

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.

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)0.011
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.423
GPT teacher head0.600
Teacher spread0.177 · 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