An Optimized Microsatellite Genotyping Strategy for Assessing Genetic Identity and Kinship in Azara’s Owl Monkeys (Aotus azarai)
Bibliographic record
Abstract
In this study, we characterize a panel of 20 microsatellite markers that reproducibly amplify in Azara's owl monkeys (Aotus azarai) for use in genetic profiling analyses. A total of 128 individuals from our study site in Formosa, Argentina, were genotyped for 20 markers, 13 of which were found to be polymorphic. The levels of allelic variation at these loci provided paternity exclusion probabilities of 0.852 when neither parent was known, and 0.981 when one parent was known. In addition, our analysis revealed that, although genotypes can be rapidly scored using fluorescence-based fragment analysis, the presence of complex or multiple short tandem repeat (STR) motifs at a microsatellite locus could generate similar fragment patterns from alleles that have different nucleotide sequences and perhaps different evolutionary origins. Even so, this collection of microsatellite loci is suitable for parentage analyses and will allow us to test various hypotheses about the relationship between social behavior and kinship in wild owl monkey populations. Furthermore, given the limited number of platyrrhine-specific microsatellite loci available in the literature, this STR panel represents a valuable tool for population studies of other cebines and callitrichines.
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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".