Visual detection and fruit selection by the mantled howler monkey (<i>Alouatta palliata</i>)
Bibliographic record
Abstract
Howler monkeys (platyrrhini) have evolved routine trichromatic color vision independently from catarrhines, which presents an opportunity to test hypotheses concerning the adaptive value of distinguishing reddish from greenish hues. A longstanding hypothesis posits that trichromacy aids in the efficient detection of reddish-ripe fruits, which could be an advantage for the detection of the nutritional content of the fruit, such as sugars. In the present study, we assessed fruit visual conspicuity and selection based on color and sucrose content by wild mantled howler monkeys (Alouatta palliata) on Agaltepec Island, Mexico. We used colorimetry to classify dietary fruits as cryptic (greenish) or conspicuous (reddish) against their background leaves. Species-specific color models indicate that trichromatic howler monkeys should be more efficient in discriminating the conspicuous ripe fruits from leaves compared to detecting cryptic ripe fruits from leaves. We found howler monkeys consume more cryptic fruits compared to conspicuous fruits, and that they consume more unripe fruits than ripe fruits. The consumption (acceptance) of fruit was independent of sucrose content, and thus this disaccharide may not play an essential role in mantled howler food selection. Our findings suggest that routine trichromatic color vision may aid in the detection and discrimination of conspicuously colored fruits, but that the final decision whether to accept or reject a fruit probably involves the use of other senses in addition to vision.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".