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Record W2333952623 · doi:10.1017/s0317167100005527

Consent in Alzheimer's Disease Research: Risk/Benefit Factors

2007· review· en· W2333952623 on OpenAlexaffvenue
B. Lynn Beattie

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2007
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiseaseAnticipation (artificial intelligence)MedicineDisadvantagedPopulationInformed consentRealmBiobankPsychologyIntensive care medicineAlternative medicineEnvironmental healthBioinformaticsPolitical sciencePathology

Abstract

fetched live from OpenAlex

In the era of chronic disease, we are challenged to find therapies that provide symptomatic relief and ideally, alter the course of the underlying disease. In Alzheimer's disease (AD), these issues are complicated by the disease itself, which affects the subject's decision-making capacity for participation in the research. According to established ethical guidelines it is clear that individuals with impaired capacity may participate in research and their risk should be no greater than that which the individual would have in day to day activities with anticipation of benefits within that realm. Decision making processes are complex and involve proxies who themselves have biases about their loved one and the potential for participating in the research. Newer disease-modifying approaches such as immunotherapy have potential for affecting the course of the underlying disease but with greater risk of more significant side effects. Ideally the health care of the subjects is not disadvantaged by research participation. At the same time, trials of potentially riskier therapy are relevant in subjects with the disease. Research for subjects with AD must have appropriate safeguards in place to enable effective progress in innovative therapy for a vulnerable, often elderly population. Recommendations are made which could further our capacity to undertake ethical research in the AD population.

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)0.059
metaresearch head score (Gemma)0.091
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0590.091
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0060.006
Science and technology studies0.0030.027
Scholarly communication0.0010.001
Open science0.0050.000
Research integrity0.0010.020
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 head0.756
GPT teacher head0.585
Teacher spread0.171 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations14
Published2007
Admission routes2
Has abstractyes

Explore more

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