Shorebirds’ Longer Migratory Distances Are Associated With Larger ADCYAP1 Microsatellites and Greater Morphological Complexity of Hippocampal Astrocytes
Bibliographic record
Abstract
For the epic journey of autumn migration, long-distance migratory birds use innate and learned information and follow strict schedules imposed by genetic and epigenetic mechanisms, the details of which remain largely unknown. In addition, bird migration requires integrated action of different multisensory systems for learning and memory, and the hippocampus appears to be the integration center for this task. In previous studies we found that contrasting long-distance migratory flights differentially affected the morphological complexity of two types of hippocampus astrocytes. Recently, a significant association was found between the latitude of the reproductive site and the size of the ADCYAP1 allele in long distance migratory birds. We tested for correlations between astrocyte morphological complexity, migratory distances, and size of the ADCYAP1 allele in three long-distance migrant species of shorebird and one non-migrant. Significant differences among species were found in the number and morphological complexity of the astrocytes, as well as in the size of the microsatellites of the ADCYAP1 gene. We found significant associations between the size of the ADCYAP1 microsatellites, the migratory distances, and the degree of morphological complexity of the astrocytes. We suggest that associations between astrocyte number and morphological complexity, ADCYAP1 microsatellite size, and migratory behavior may be part of the adaptive response to the migratory process of shorebirds.
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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 | 0.000 |
| 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 | 0.000 |
| 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".