Microsatellite analysis reveals substantial levels of genetic variation but low levels of genetic divergence among isolated populations of Kaka (<i>Nestor meridionalis</i>)
Bibliographic record
Abstract
The Kaka (Nestor meridionalis) is a threatened, endemic forest parrot of New Zealand with a fragmented distribution. We present data from eight microsatellite DNA loci for 126 Kaka from nine locations along the length of New Zealand. The observed patterns of variation reveal little population structure in Kaka, despite substantial levels of genetic variation. Our estimate of RST over all populations is low (0.04) and a hierarchical analysis of molecular variance (AMOVA) shows that most allelic variation (93.7%) is within populations rather than divided among them. Further, most inter-population genetic differentiation is attributed to the divergence of the possibly bottlenecked Kapiti Island population from all other populations surveyed. This overall homogeneity probably reflects historic population structure and is being maintained by the ongoing dispersal of individuals between populations. Conservation management of Kaka should reflect this New Zealand-wide gene flow, although special consideration may be given to Kapiti Island.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".