Bibliographic record
Abstract
Aim. Both single-unit recording studies in V1 and psychophysical studies have revealed orientation-selective mechanisms whose length selectivity is partially separable from their width or spatial frequency selectivity. This suggests that length might be a spatial dimension coded early in vision. If so, one would expect line length to be adaptable, with adaptation producing shifts in the perceived length of subsequently presented lines. Method. Subjects adapted to horizontal d.c.-balanced lines of various lengths, presented either singly or in grids. After adaptation, the perceived length of horizontal test lines that were either shorter or longer than the adaptors was measured using a conventional staircase procedure. To test whether any after-effect of perceived length was a manifestation of the well-known size or spatial-frequency after-effect, we also used vertically-oriented square-wave grating adaptors whose bars were equal in width to the length of the adaptor lines. Results. Adaptation to line length made shorter lines appear shorter and longer lines appear longer, analogous to the repulsion effects found with other spatial dimensions such as orientation and spatial frequency. With square-wave grating adaptors however, the after-effect was much smaller. Conclusion. Line length is an adaptable dimension and the resulting line-length after-effect is not simply a manifestation of the size or spatial-frequency after-effect. Line length appears to be a spatial dimension that is likely coded through the population response of neurons tuned to similar widths but different lengths.
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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 | 0.002 |
| 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) | 0.004 | 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".