The Antipointing Task: Vector Inversion Is Supported by a Perceptual Estimate of Visual Space
Bibliographic record
Abstract
The authors examined whether the visual field-specific endpoint bias of mirror-symmetrical reaching movements (i.e., antipointing) is related to top-down decoupling of the normal spatial relations between target and response (i.e., visuomotor inhibition) or the inversion of target coordinates to a mirror-symmetrical location (i.e., vector inversion). Participants completed pro- and antipointing movements in left and right visual space under conditions in which movement type was performed in separate blocks (i.e., blocked condition) and when randomly interleaved on a trial-by-trial basis (i.e., random condition). Most important, the random condition entailed equivalent premovement inhibition across pro- and antipointing. Propointing produced comparable endpoint accuracy in left and right visual space whereas antipointing under- and overshot target position: a finding characterizing blocked and random conditions. The authors attribute the visual field-specific bias of antipointing to the obligatory nature of the task and the integration of visuoperceptual networks to support vector inversion.
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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 | 0.007 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".