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Record W3138847939 · doi:10.1016/j.cortex.2021.03.006

Recognition memory and divergent cognitive profiles in prodromal genetic frontotemporal dementia

2021· article· en· W3138847939 on OpenAlexafffund
Megan S. Barker, Masood Manoochehri, Sandra Rizer, Brian S. Appleby, Danielle Brushaber, Sheena I. Dev, Katrina L. Devick, Bradford C. Dickerson, Julie A. Fields, Tatiana Foroud, Leah K. Forsberg, Douglas Galasko, Nupur Ghoshal, Neill R. Graff‐Radford, Murray Grossman, Hilary W. Heuer, Ging‐Yuek Robin Hsiung, John Kornak, Irene Litvan, Ian R. Mackenzie, Mario F. Mendez, Belén Pascual, Katherine P. Rankin, Katya Rascovsky, Adam M. Staffaroni, Maria Carmela Tartaglia, Sandra Weıntraub, Bonnie Wong, Bradley F. Boeve, Adam L. Boxer, Howard J. Rosen, Jill Goldman, Edward D. Huey, Stephanie Cosentino

Bibliographic record

VenueCortex · 2021
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNational Institute of Mental HealthNational Institute on AgingCanadian Institutes of Health ResearchParkinsonfondenUniversity of California, San DiegoNational Institutes of HealthEisaiParkinson Study GroupRainwater Charitable FoundationAbbVieMayo ClinicBiogenNational Center for Advancing Translational SciencesRocheCenters for Disease Control and PreventionNovartisQuest DiagnosticsAssociation for Frontotemporal DegenerationAlzheimer SocietyBristol-Myers SquibbMichael J. Fox Foundation for Parkinson's Research
KeywordsFrontotemporal dementiaPsychologyEpisodic memoryC9orf72CognitionSemantic memoryDementiaVerbal memoryExecutive dysfunctionNeuropsychologyCognitive psychologyNeuroscienceDiseaseMedicine

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)0.001
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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

Citations39
Published2021
Admission routes2
Has abstractno

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