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Record W3173679554 · doi:10.3389/frym.2021.706131

Distracted? Blame Your Claustrum!

2021· article· en· W3173679554 on OpenAlexaff
Yonatan Fatal, Ami Citri

Bibliographic record

VenueFrontiers for Young Minds · 2021
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsClaustrumPsychologySilenceBlameSightVariety (cybernetics)Cognitive psychologySocial psychologyNeuroscienceComputer scienceArtificial intelligenceAestheticsArt

Abstract

fetched live from OpenAlex

To succeed in reading these sentences, your brain must ignore a variety of distractions—sights, sounds, and smells. Resisting distractions is a vital ability for our daily lives, and it poses a unique challenge for people who are dealing with attention disorders. In a recent study, we asked whether an area in the brain called the claustrum supports the ability to ignore distractions. We developed methods that allowed us to silence the claustrum in mice. We challenged these mice with tasks requiring them to pay attention. We found that mice whose claustra were silenced were especially sensitive to distractions. These results provide an important clue about the function of the claustrum, and we hope that they will contribute to the development of new methods that will assist people dealing with attention disorders.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.081
GPT teacher head0.311
Teacher spread0.230 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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