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Record W2014828742 · doi:10.1002/sim.1720

Two macroscopic and microscopic brain imaging studies of human hippocampus in early Alzheimer's disease and schizophrenia research

2004· article· en· W2014828742 on OpenAlexaff
Nicholas Lange, Stephen Lake, Reisa A. Sperling, John Brown, Carol Routledge, Marilyn Albert, Stephan Heckers

Bibliographic record

VenueStatistics in Medicine · 2004
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSmiths Detection (Canada)
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institutes of Health
KeywordsNeuroscienceSchizophrenia (object-oriented programming)Hippocampal formationHippocampusHuman brainFunctional magnetic resonance imagingDiseaseBrain Structure and FunctionPsychologyAlzheimer's diseaseNeuroimagingMedicinePsychiatryPathology

Abstract

fetched live from OpenAlex

Among the many diseases that affect the hippocampus, a small yet highly important brain region responsible for memory and identity, Alzheimer's disease and schizophrenia are among the most devastating. We describe a two-stage, region-of-interest based linear mixed model approach to the analysis of a longitudinal functional magnetic resonance (FMRI) study of human memory function under several drug challenges. We then describe a Monte Carlo approach to testing members of nested hierarchies of linear models in a stereological study of different types and locations of human hippocampal neurons. Last, we attempt to draw the attention of the biostatistical community interested in imaging neuroscience to the intriguing complexities of human hippocampal research in early Alzheimer's disease, schizophrenia and other brain diseases via brain imaging methods.

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 distilled prediction

Teacher imitation

Not 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)0.001
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.425
Teacher spread0.340 · 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 teacher head, not a consensus.

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

Citations8
Published2004
Admission routes1
Has abstractyes

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