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Record W3217297165 · doi:10.1002/acp.3904

Lifestyle factors and their impact on the networks of attention

2021· article· en· W3217297165 on OpenAlexaff
Colin R. McCormick

Bibliographic record

VenueApplied Cognitive Psychology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyCognitionPremisePsychological interventionAttention networkCognitive psychologyMeditationExecutive functionsPsychiatry

Abstract

fetched live from OpenAlex

Abstract In 2002, Fan and his colleagues developed the Attention Network Test (ANT), a cognitive tool that provides a score for each of the attentional networks (alerting, orienting, and executive functioning). Since publication, this study has been cited over 3 500 times. The authors state one of the indicated uses of this tool is to measure how different interventions, both behavioral and pharmacological, influence the networks of attention. The present review focuses on this premise and investigates how various aspects of lifestyle differently impact the networks of attention. Whether trying to optimize the attentional networks to improve cognitive performance, or to prevent the cognitive decline that occurs with age, this review summarizes what practices promote efficiency within the alerting, orienting, and executive functioning networks. The specific areas of lifestyle this review focuses on are meditation, exercise, drug use, sleep, and environmental or social factors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.379

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 studies0.0000.001
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 head0.111
GPT teacher head0.381
Teacher spread0.271 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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