Hitting the Target: Relatively Easy, Yet Absolutely Difficult
Bibliographic record
Abstract
It is generally agreed that absolute-direction judgments require information about eye position, whereas relative-direction judgments do not. The source of this eye-position information, particularly during monocular viewing, is a matter of debate. It may be either binocular eye position, or the position of the viewing-eye only, that is crucial. Using more ecologically valid stimulus situations than the traditional LED in the dark, we performed two experiments. In experiment 1, observers threw darts at targets that were fixated either monocularly or binocularly. In experiment 2, observers aimed a laser gun at targets while fixating either the rear or the front gunsight monocularly, or the target either monocularly or binocularly. We measured the accuracy and precision of the observers' absolute- and relative-direction judgments. We found that (a) relative-direction judgments were precise and independent of phoria, and (b) monocular absolute-direction judgments were inaccurate, and the magnitude of the inaccuracy was predictable from the magnitude of phoria. These results confirm that relative-direction judgments do not require information about eye position. Moreover, they show that binocular eye-position information is crucial when judging the absolute direction of both monocular and binocular targets.
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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 | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".