MétaCan
Menu
Back to cohort
Record W4402840847 · doi:10.70270/fjmsmbv

New Frontiers in Alzheimer's Support

2024· article· en· W4402840847 on OpenAlexaboutno aff
Andrew Haller

Bibliographic record

VenueMednet · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCognitive science

Abstract

fetched live from OpenAlex

Alzheimer’s disease (AD) and related dementia diagnoses are very prevalent in Canada. Approximately 733,040 people in Canada are currently living with dementia, and that number is estimated to grow to nearly 1 million Canadians by 2030. (1) AD is the most common type of dementia, an overall term for conditions that cause problems with memory, thinking and behaviour. In the early stage, dementia symptoms may be minimal, but as the disease causes more damage to the brain, symptoms worsen. The rate at which the disease progresses is different for everyone, but on average, people with AD live for roughly eight years after symptoms begin.

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)0.007
metaresearch head score (Gemma)0.012
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: Review · Consensus signal: none
Teacher disagreement score0.223
Threshold uncertainty score0.746

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0090.006
Open science0.0020.005
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.2230.043

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 head0.016
GPT teacher head0.261
Teacher spread0.245 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMednetSame topicHealth, Environment, Cognitive AgingFrench-language works237,207