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Record W7132879477

Early Detection of Polyneuropathy in Patients with Hereditary Transthyretin Amyloid Cardiomyopathy and Determining the Cost-Effective Treatment for Mixed Phenotype Patients

2024· dissertation· W7132879477 on OpenAlexaff
Priya Arivalagan

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransthyretinAmyloidosisPolyneuropathyAmyloid polyneuropathyCardiomyopathyCardiac amyloidosisAmyloid (mycology)DiseaseTetramer
DOInot available

Abstract

fetched live from OpenAlex

Transthyretin amyloidosis is a rare disease caused by the deposits of misfolded proteins known as amyloid. This disease is caused by misfolded transthyretin (TTR) proteins, that are produced in the liver and are deposited in various organs and tissues, especially in the heart and nerves. These TTR proteins are normally formed as stable tetramers; however, a mutation on the TTR gene could cause the dissociation of the TTR tetramer into monomers which would then form as TTR amyloid causing transthyretin amyloidosis (ATTR). Patients with ATTR may present cardiomyopathy and/or polyneuropathy. Although there is no cure for this disease, there are treatments available that would slow down the progression of ATTR and allow patients to have a better quality of life (QOL). The treatments include organ transplantation (liver/heart) or novel disease modifying therapies. This thesis focuses on detecting polyneuropathy among patients with hereditary transthyretin amyloid cardiomyopathy and determining its cost-effective treatment.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.001

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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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