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Record W1870284349 · doi:10.1002/jnr.23552

Motor activity in young <i>APP<sub>swe</sub> + PS1</i>/A246E bigenic mice as a predicting variable for memory decline

2015· article· en· W1870284349 on OpenAlexaff
Mohammed Filali, Robert Lalonde

Bibliographic record

VenueJournal of Neuroscience Research · 2015
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsNeuropathologyOpen fieldNeuroscienceCognitionPsychologyMedicineRecognition memoryPhysiologyDevelopmental psychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Reports of individuality in rodent species have been a subject of debate in pharmacology and other fields. In the current study, APPswe + PS1/A246E bigenic mice with Alzheimer's-like pathogenesis and wild-type controls were subdivided at 3 months of age into low, intermediate, and high responders in open-field activity. The mice were then evaluated longitudinally at 3 and 9 months for object recognition. Irrespective of genotype, mice with a high level of motor activity had better scores in object recognition. However, a significant correlation was established between open-field activity measured at 3 months of age and recognition memory measured at 9 months of age in the bigenic group only. These results indicate that motor activity in young mice with amyloid neuropathology may serve as a predicting variable for cognitive dysfunction in more mature mice.

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)0.008
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.135
GPT teacher head0.425
Teacher spread0.291 · 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 designBench or experimental
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

Citations4
Published2015
Admission routes1
Has abstractyes

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