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Record W2115849200 · doi:10.1016/j.jalz.2006.02.005

Should older adults be screened for dementia?

2006· article· en· W2115849200 on OpenAlexaff
J. Wesson Ashford, Soo Borson, Ruth O’Hara, Paul Dash, Lori Frank, Philippe Robert, William R. Shankle, Mary C. Tierney, Henry Brodaty, Frederick A. Schmitt, Helena C. Kraemer, Herman Buschke

Bibliographic record

VenueAlzheimer s & Dementia · 2006
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute on AgingNational Institutes of Health
KeywordsDementiaGerontologyPsychologyMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

The question of whether to screen for dementia and Alzheimer's disease (AD) has been discussed in many forums throughout the world. Generally, medical advisory groups and policy-making groups have recognized the importance of early diagnosis but have uniformly avoided making recommendations to screen at-risk populations. This presentation reflects the support for reconsidering the importance of screening individuals at risk or above a certain age. In this statement, the majority of the authors support the consideration of dementia risk factors in individuals at age 50, with routine yearly screening after 75. Other authors remain concerned that the benefits of treatments of early disease do not yet support a general screening recommendation. These statements are made to encourage progress toward the development of a consensus regarding the widespread institution of screening policy. Accordingly, members of the worldwide scientific community are invited to add their perspective by contributing short commentaries (1500 words) on this subject.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.038
GPT teacher head0.325
Teacher spread0.287 · 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 teacher head, not a consensus.

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

Citations76
Published2006
Admission routes1
Has abstractyes

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