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Record W3018431352 · doi:10.1016/s1474-4422(20)30071-5

Blood phosphorylated tau 181 as a biomarker for Alzheimer's disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts

2020· article· en· W3018431352 on OpenAlexafffund
Thomas K. Karikari, Tharick A. Pascoal, Nicholas J. Ashton, Shorena Janelidze, Andréa Lessa Benedet, Juan Lantero‐Rodriguez, Mira Chamoun, Mélissa Savard, Min Su Kang, Joseph Therriault, Michael Schöll, Gassan Massarweh, Jean-Paul Soucy, Kina Höglund, Gunnar Brinkmalm, Niklas Mattsson, Sebastian Palmqvist, Serge Gauthier, Erik Stomrud, Henrik Zetterberg, Oskar Hansson, Pedro Rosa‐Neto, Kaj Blennow

Bibliographic record

VenueThe Lancet Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersEuropean Research CouncilFonds de Recherche du Québec - SantéMontreal Neurological Institute and HospitalUniversity Hospital FoundationWallenberg Centre for Molecular and Translational MedicineVetenskapsrådetHjärnfondenGE HealthcareKnut och Alice Wallenbergs StiftelseLunds UniversitetCanada Foundation for InnovationAlzheimer SocietyConsortium canadien en neurodégénérescence associée au vieillissementAlzheimer's Drug Discovery FoundationCanadian Institutes of Health ResearchAlzheimerfondenWeston Brain InstituteSahlgrenska UniversitetssjukhusetRocheMarcus och Amalia Wallenbergs minnesfondParkinson Research FoundationAssociation for Frontotemporal Degeneration
KeywordsMedicineBiomarkerCohortDementiaProspective cohort studyInternal medicineOncologyDiseaseCohort studyCognitive declineFrontotemporal dementiaAlzheimer's disease

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.017
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.127
GPT teacher head0.338
Teacher spread0.210 · 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 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

Citations1,360
Published2020
Admission routes2
Has abstractno

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