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Record W4211165247 · doi:10.1016/j.cccb.2022.100044

What does aducanumab treatment of Alzheimer's disease mean for research on vascular cognitive disorders?

2022· editorial· en· W4211165247 on OpenAlexaff
Anders Wallin, Suvarna Alladi, Sandra E. Black, Christopher Chen, Steven M. Greenberg, Deborah Gustafson, Jeremy D. Isaacs, Hanna Jokinen, Raj N. Kalaria, Vincent Mok, Leonardo Pantoni, Florence Pasquier, Gustavo C. Román, Gary A. Rosenberg, Reinhold Schmidt, Eric E. Smith, Atticus H. Hainsworth

Bibliographic record

VenueCerebral Circulation - Cognition and Behavior · 2022
Typeeditorial
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsUniversity of CalgaryHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersMedical Research CouncilAgence Nationale de la Recherche
KeywordsObservational studyCognitionDiseaseCognitive impairmentMedicineAlzheimer's diseasePsychologyVascular dementiaDementiaPsychiatryClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

•Controversial registration of aducanumab for Alzheimer's Disease•Aducanumab is the subject of post-licensing observational studies aiming to follow the effects of the drug•Given the high prevalence of cerebrovascular pathology it is important that these studies do not ignore vascular cognitive disorders•The studies may give detailed phenotyping data that may lead to knowledge of targets for treatments of patients with vascular cognitive disorders.

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)0.012
metaresearch head score (Gemma)0.028
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.026
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0060.006
Open science0.0040.001
Research integrity0.0260.032
Insufficient payload (model declined to judge)0.0070.009

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 head0.122
GPT teacher head0.388
Teacher spread0.267 · 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
GenreEditorial

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

Citations10
Published2022
Admission routes1
Has abstractyes

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