Effective attention allocation behavior and its measurement: a preliminary study
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.
Bibliographic record
Abstract
In general, evaluation of human–machine interface design remains a challenging task. Specifically, there remains a lack of method for tracking effective human operator's attention. This paper presents a study aimed at devising such a method. This method is based on a combination of operators' eye movement and hand movement behaviors. The eye movement reflects the operators' cognitive process and attention allocation, while the hand movement reflects the operators' physical action, which is the result of a cognitive process. Effectiveness of that piece of cognition (eye movement) can therefore be evaluated based on the result of an action (hand movement). The said measure, which may be called the hand–eye measure, is examined for its sensitivity to a good or poor operation behavior and patterns that are further correlated to the operator's behavior and performance. At present, the patterns across the whole operation period are explored. A reference system is employed to validate the hand–eye measure.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it