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Record W2127226841 · doi:10.1159/000364914

The Neurosurgical Treatment of Alzheimer's Disease: A Review

2014· review· en· W2127226841 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

VenueStereotactic and Functional Neurosurgery · 2014
Typereview
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineDiseaseClinical trialIntensive care medicineDeep brain stimulationNeurosurgeryNeuroscienceSurgeryPathologyPsychologyParkinson's disease

Abstract

fetched live from OpenAlex

BACKGROUND: Alzheimer's disease (AD) is a debilitating neurological illness of increasing prevalence. Because many patients are affected and current treatments have limited effectiveness, other therapeutic strategies are urgently needed. OBJECTIVES: Here we provide a review of the neurosurgical approaches that have been attempted or are currently being investigated for the treatment of AD. METHODS: Computerized database searches identified all of the published studies in the English-language literature examining the surgical treatment of AD since 1950. RESULTS: The following 5 categories of neurosurgical treatment were identified: cerebrospinal fluid shunting, intraventricular infusions, tissue grafting, gene therapy, and electrical neural stimulation. CONCLUSIONS: While none of the neurosurgical approaches applied to the treatment of AD have proven effective to date, recent trials involving gene therapy and electrical neural stimulation are showing promising early results. Larger trials investigating these treatments have been proposed or are currently under way.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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 head0.084
GPT teacher head0.320
Teacher spread0.236 · 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