Not all probabilities are equivalent: Evidence from orientation versus spatial probability learning.
Bibliographic record
Abstract
Frequently targets are detected faster, probable locations searched earlier, and likely orientations estimated more precisely. Are these all consequences of a single, domain-general "attentional" effect? To examine this issue, participants were shown brief instances of spatial gratings, and were tasked to draw their location and orientation. Unknown to participants, either the location or orientation probability of these gratings were manipulated. While orientation probability affected the precision of orientation reports, spatial probability did not. Further, utilising lowered stimulus contrast (via a staircase procedure) and a combination of behavioral precision and confidence self-report, we clustered trials with perceived stimuli from trials where the target was not detected: Spatial probability only modulated the likelihood of stimulus detection, but not did not modulate perceptual precision. Even when no physical attentional cues are present, acquired probabilistic information on space versus orientation leads to separable 'attention-like' effects on behaviour. We discuss how this could be linked to distinct underlying neural mechanisms. (PsycINFO Database Record
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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 | 0.004 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".