Collinear search impairment is luminance contrast invariant
Bibliographic record
Abstract
Collinear search impairment (CSI) is a phenomenon where a task-irrelevant collinear structure impairs a target search in a visual display. It has been suggested that CSI is monocular, occurs without the participants' access to consciousness and is possibly processed at an early visual site (e.g. V1). This effect has frequently been compared with a well-documented opposite effect called attentional capture (AC), in which salient and task-irrelevant basic features (e.g. color, orientation) enhance target detection. However, whether this phenomenon can be attributed to non-attentional factors such as collinear facilitation (CF) has not yet been formally tested. Here we used one well-established property of CF, i.e. that target contrast modulates its effect direction (facilitation vs suppression), to examine whether CSI shared similar signature profiles along different contrast levels. In other words, we tested whether CSI previously observed at the supra-threshold level was reduced or reversed at near-threshold contrast levels. Our results showed that, regardless of the luminance contrast levels, participants spent a longer time searching for targets displayed on the salient singleton collinear structure than those displayed off the structure. Contrast invariance suggests that it is unlikely that CSI is exclusively sub-served by an early vision mechanism (e.g. CF).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".