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Record W2429544251 · doi:10.1111/jnc.13588

Molecular neuropathology of frontotemporal dementia: insights into disease mechanisms from postmortem studies

2016· review· en· W2429544251 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Neurochemistry · 2016
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsVancouver General HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchDirektion für Entwicklung und Zusammenarbeit
KeywordsNeuropathologyFrontotemporal dementiaDementiaDiseasePostmortem studiesNeuroscienceMedicinePathologyPsychology

Abstract

fetched live from OpenAlex

Frontotemporal dementia (FTD) is a clinical syndrome with a heterogeneous molecular basis. The past decade has seen the discovery of several new FTD-causing genetic mutations and the identification of many of the relevant pathological proteins. The current neuropathological classification is based on the predominant protein abnormality and allows most cases of FTD to be placed into one of three broad molecular subgroups; frontotemporal lobar degeneration with tau, TDP-43 or FET protein accumulation. This review will describe our current understanding of the molecular basis of FTD, focusing on insights gained from the study of human postmortem tissue, as well as some of the current controversies. Most cases of FTD can be subclassified into one of three broad molecular subgroups based on the predominant protein that accumulates as pathological cellular inclusions. Understanding the associated pathogenic mechanisms and recognizing these FTD molecular subtypes in vivo will likely be crucial for the development and use of targeted therapies. This article is part of the Frontotemporal Dementia special issue.

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 score0.687
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.373
Teacher spread0.319 · 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