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Record W1980627155 · doi:10.1080/13854046.2013.851741

Evaluation of a 10-minute Version of the Attention Network Test

2013· article· en· W1980627155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Clinical Neuropsychologist · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsNipissing UniversityLakehead UniversitySt. Joseph's Care GroupNOSM University
FundersAUTO21 Network of Centres of ExcellenceNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchOntario Neurotrauma Foundation
KeywordsTest (biology)Computer sciencePsychologyGeology

Abstract

fetched live from OpenAlex

The widely used Java version of the Attention Network Test (ANT), which can be downloaded from https://www.sacklerinstitute.org/cornell/assays_and_tools/ , takes approximately 20 minutes to complete. A shorter version would be useful in clinical or applied research settings where many tests are administered. We assessed how well a new 10-minute version of the ANT agrees with the 20-minute version. Response time (RT) measures from the shorter version correlated very highly with the corresponding measures from the 20-minute version (Pearson correlations ranging from .88 to .92). Therefore RT measures from the shorter version can safely be used in place of those same measures from the 20-minute version. Correlations for the three network scores (alerting, orienting and conflict efficiency) were not as strong (range = .10 to .53). This is not surprising, given that the network scores are difference scores. Further research is needed to determine whether adequate reliability can be achieved for the network scores without unduly increasing the length of the task.

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.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.396
GPT teacher head0.478
Teacher spread0.082 · 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