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Record W2070243746 · doi:10.1586/17512433.2013.811237

Novel disease-modifying therapeutics for the treatment of Alzheimer’s disease

2013· review· en· W2070243746 on OpenAlex
Gabriel C. Léger, Fadi Massoud

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

VenueExpert Review of Clinical Pharmacology · 2013
Typereview
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineDiseaseMemantineClinical trialDementiaIntensive care medicineMechanism (biology)Drug developmentDrugPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Alzheimer's disease is the most common cause of dementia and is becoming a global health concern. Despite a well-established understanding of the molecular mechanism involved in its pathogenesis, and millions of dollars of investment in drug discovery and clinical trials, no single molecule has yet been approved for its treatment since the advent of cholinesterase inhibitors and memantine. This review examines first the optimal use of currently approved agents and then explores in detail the current Phase II and III clinical trial landscape, while spending some time on the mechanistic details. Driven by the increasing knowledge gleaned from numerous Phase III failures and improvements in early detection and biomarkers, there is renewed enthusiasm that a cure is taking shape along the visible horizon.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.453
GPT teacher head0.605
Teacher spread0.152 · 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