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The effect of increased genetic risk for Alzheimer's disease on hippocampal and amygdala volume
Michelle K. Lupton, Lachlan T. Strike, Narelle K. Hansell, Wei Wen, Karen A. Mather, Nicola J. Armstrong, Anbupalam Thalamuthu, Katie L. McMahon, Greig I. de Zubicaray, Amelia A. Assareh, Andrew Simmons, Petroula Proitsi, John Powell, Grant W. Montgomery, Derrek P. Hibar, Eric Westman, Magda Tsolaki, Iwona Kłoszewska, Hilkka Soininen, Patrizia Mecocci, Bruno Velas, Simon Lovestone, Henry Brodaty, David Ames, Julian N. Trollor, Nicholas G. Martin, Paul M. Thompson, Perminder S. Sachdev, Margaret J. Wright
Bibliographic record
VenueNeurobiology of Aging · 2016
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Cancer InstituteNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Health and Medical Research CouncilMenzies Centre for Australian Studies, King's College London, University of LondonJohn and Lucille Van Geest FoundationIXICOFujirebio EuropeLabexMedical Research CouncilServierKuopion Yliopistollinen SairaalaMedpaceBundesministerium für Bildung und ForschungUniversity of Southern CaliforniaEisaiInstitute Pasteur De LilleCentre hospitalier régional universitaire de LilleAlzheimer’s Research UKNational Institute of Biomedical Imaging and BioengineeringUniversity of MelbourneInstitut National de la Santé et de la Recherche MédicaleGenentechEuropean CommissionGE HealthcareAcademy of FinlandKing's College LondonGuy's and St Thomas' CharityU.S. Department of DefenseCommonwealth Scientific and Industrial Research OrganisationNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchAlzheimer's SocietyUniversity of California, San DiegoDevelopment of Innovative Strategies for a Transdisciplinary approach to ALZheimer's diseaseBiogenNational Computational InfrastructureHjartaverndMaudsley CharityNorthern California Institute for Research and EducationPfizerAustralian Research CouncilBioClinicaF. Hoffmann-La RocheWellcome TrustWellcomeSynarcNational Center for Advancing Translational SciencesNovartis Pharmaceuticals CorporationTakeda Pharmaceutical CompanyUniversité de LilleErasmus Medisch CentrumBiogen IdecAlzheimer's Research TrustNational Institute of Child Health and Human DevelopmentEli Lilly and CompanyBristol-Myers SquibbMerckNational Institutes of HealthAlzheimer's Drug Discovery FoundationDementia Australia Research FoundationAlzheimer's AssociationAlzheimer's Disease Neuroimaging InitiativeMeso Scale Diagnostics
KeywordsAmygdalaApolipoprotein EHippocampal formationHippocampusMedicineDementiaAlzheimer's diseaseBrain sizeSingle-nucleotide polymorphismPsychologyPopulationInternal medicineDiseaseMagnetic resonance imagingNeuroscienceOncologyBiologyGenotypeGeneticsGene
Abstract
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 distilled prediction
Teacher imitationNot 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.266
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.011
GPT teacher head0.282
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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
Citations133
Published2016
Admission routes1
Has abstractno