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Record W2922067124 · doi:10.14283/jpad.2019.2

Report from the First Clinical Trials on Alzheimer's Disease (CTAD) Asia-China 2018 : Bringing together Global Leaders

2019· article· en· W2922067124 on OpenAlexaff
Jagadish K. Chhetri, Pak To Chan, Bruno Vellas, J. Touchon, Serge Gauthier

Bibliographic record

VenueThe Journal of Prevention of Alzheimer s Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsChinaContext (archaeology)DiseasePopulationPopulation ageingMedicineClinical trialPolitical scienceGeographyEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Population of older adults in Asia, and particularly in China is increasing rapidly. Older population are at increased risk of Alzheimer's disease (AD) and other dementias. Soon, the Chinese population with AD will represent almost half of the world's AD population. There is a desperate need of disease modifying therapies to delay or slow the progression of AD, to tackle this emerging healthcare emergency. In this context, the first CTAD Asia-China conference was held in China to bring together Western and Asian leaders in AD. This meeting focused largely on how to develop successful trials in China, utilizing past experiences from the West.

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)0.023
metaresearch head score (Gemma)0.023
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: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0140.006

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 head0.123
GPT teacher head0.439
Teacher spread0.316 · 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
GenreOther

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

Citations8
Published2019
Admission routes1
Has abstractyes

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Same venueThe Journal of Prevention of Alzheimer s DiseaseSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207