Importance of Achromatic Contrast in Short-Range Fruit Foraging of Primates
Bibliographic record
Abstract
Trichromatic primates have a 'red-green' chromatic channel in addition to luminance and 'blue-yellow' channels. It has been argued that the red-green channel evolved in primates as an adaptation for detecting reddish or yellowish objects, such as ripe fruits, against a background of foliage. However, foraging advantages to trichromatic primates remain unverified by behavioral observation of primates in their natural habitats. New World monkeys (platyrrhines) are an excellent model for this evaluation because of the highly polymorphic nature of their color vision due to allelic variation of the L-M opsin gene on the X chromosome. In this study we carried out field observations of a group of wild, frugivorous black-handed spider monkeys (Ateles geoffroyi frontatus, Gray 1842, Platyrrhini), consisting of both dichromats (n = 12) and trichromats (n = 9) in Santa Rosa National Park, Costa Rica. We determined the color vision types of individuals in this group by genotyping their L-M opsin and measured foraging efficiency of each individual for fruits located at a grasping distance. Contrary to the predicted advantage for trichromats, there was no significant difference between dichromats and trichromats in foraging efficiency and we found that the luminance contrast was the main determinant of the variation of foraging efficiency among red-green, blue-yellow and luminance contrasts. Our results suggest that luminance contrast can serve as an important cue in short-range foraging attempts despite other sensory cues that could be available. Additionally, the advantage of red-green color vision in primates may not be as salient as previously thought and needs to be evaluated in further field observations.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".