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Record W2711696676

Advances in understanding Alzheimer's disease, and the contributions of current Alzheimer research: ten years on and beyond

2014· article· en· W2711696676 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

VenueIUScholarWorks (Indiana University) · 2014
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsDementiaDiseasePresentation (obstetrics)Public healthGerontologyMedicinePsychiatryPsychologyPathology
DOInot available

Abstract

fetched live from OpenAlex

The initial issue of Current Alzheimer Research (CAR) was first published in 2004, a year marked by the glories of the Athens Summer Olympics as well as the destruction of the Asian Tsunami[1]. Over the last decade, scientific knowledgehas moved rapidly forward across numerous disciplines,marked by the discovery of the potential for water and life on Mars [2,3], the generation of the first induced pluripotent stem cells [4], the creation of the first cell controlled by a synthetic genome [5], and genome editing [6].In the realm of dementia -now, beyond the centennial of the first presentation by Alois Alzheimer on the disease that bears his name [7]–important changes too have occurred in the past decade. Whereas the exact prevalence of dementia remains unknown, it is crystal clear that dementia is a common, devastating and costly condition amongst the elderly. The WHO 2012 Report “Dementia: a public health priority” [8] estimatesthat 35.6 million people suffered with dementia worldwide in 2010. An estimated incidence that is much higher than that approximatedin 2004 (18 million people [9]),and this value has undoubtedly grown still more in 2014.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.076
GPT teacher head0.342
Teacher spread0.266 · 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