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Record W2896586627

[Frontotemporal dementia : an update].

2017· article· en· W2896586627 on OpenAlexaff
Cecilia Ferrer Soler, Vagia Giatrakou, Sonia Papa, Max Scheffler, Giovanni B. Frisoni

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsFrontotemporal dementiaMedicineDementiaPsychiatryHumanitiesDiseasePhilosophyPathology
DOInot available

Abstract

fetched live from OpenAlex

Frontotemporal dementia is a health issue that encompasses different specialties. This type of dementia is underdiagnosed and usually confused initially with psychiatric pathologies. Its clinical aspect as well as its evolution is a challenge for the physician on a daily basis due to the heterogeneity of the various forms. The diagnosis is usually uncertain and the current treatment can only treat the symptoms. The care of the patient and his entourage must be done in a multidisciplinary way. The advancement of research in its later years has brought to light genetic mutations that have led to a better understanding of pathology and pathophysiology. In the near future, these discoveries could lead to new targeted therapies.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.015

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 head0.082
GPT teacher head0.319
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

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 designNot applicable
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

Citations2
Published2017
Admission routes1
Has abstractyes

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