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Record W3048073772 · doi:10.1093/chemse/bjaa052

Better Olfactory Performance and Larger Olfactory Bulbs in a Mouse Model of Congenital Blindness

2020· article· en· W3048073772 on OpenAlexafffund
Sara Touj, Samie Cloutier, Amel Jemâa, Mathieu Piché, Gilles Bronchti, Syrina Al Aïn

Bibliographic record

VenueChemical Senses · 2020
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOlfactory systemSensory systemNeuroscienceOdorStimulus modalityNeuroplasticityOlfactionBlindnessOlfactory memoryPsychologyBiologyOlfactory bulbCentral nervous systemMedicine

Abstract

fetched live from OpenAlex

It is well established that early blindness results in enhancement of the remaining nonvisual sensory modalities accompanied by functional and anatomical brain plasticity. While auditory and tactile functions have been largely investigated, the results regarding olfactory functions remained less explored and less consistent. In the present study, we investigated olfactory function in blind mice using 3 tests: the buried food test, the olfactory threshold test, and the olfactory performance test. The results indicated better performance of blind mice in the buried food test and odor performance test while there was no difference in the olfactory threshold test. Using histological measurements, we also investigated if there was anatomical plasticity in the olfactory bulbs (OB), the most salient site for olfactory processing. The results indicated a larger volume of the OB driven by larger glomerular and granular layers in blind mice compared with sighted mice. Structural plasticity in the OB may underlie the enhanced olfactory performance in blind 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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.184
GPT teacher head0.247
Teacher spread0.063 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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