Evaluation of a 10-minute Version of the Attention Network Test
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".