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Record W4388758092 · doi:10.1101/lm.053840.123

Serial reversal learning in an olfactory discrimination task in 3xTg-AD mice

2023· article· en· W4388758092 on OpenAlexafffund
Kyle M. Roddick, Heather M. Schellinck, Richard E. Brown

Bibliographic record

VenueLearning & Memory · 2023
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyOdorAudiologyDiscrimination learningOlfactionDevelopmental psychologyOlfactometerNeuroscienceMedicineBiology

Abstract

fetched live from OpenAlex

Male and female 3xTg-AD mice between 5 and 24 mo of age and their B6129F2/J wild-type controls were tested on a series of 18 olfactory discrimination and reversal tasks in an operant olfactometer. All mice learned the odor discriminations and reversals to a criterion of 85% correct, but the 3xTg-AD mice made fewer errors than the B6129F2/J mice in the odor discriminations and in the first six reversal learning tasks. Many mice showed evidence of near errorless learning, and on the reversal tasks the 3xTg-AD mice showed more instances of near errorless learning than the B6129F2/J mice. There was no evidence of an age effect on odor discrimination, but there was a decrease in errorless reversal learning in aged B6129F2/J mice. In long-term memory tests, there was an increase in the number of errors made but no genotype difference. The high level of performance indicates that the mice were able to develop a "learning to learn" strategy. The finding that the 3xTg-AD mice outperformed their littermate controls provides an example of paradoxical functional facilitation in these 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 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.132
GPT teacher head0.296
Teacher spread0.164 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

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