Within-drainage population genetic structure of the freshwater fish <i>Pseudomugil signifer</i> (Pseudomugilidae) in northern Australia
Bibliographic record
Abstract
Dendritic channel patterns have the potential to isolate populations within drainages, depending on the relative position within the stream hierarchy of the populations. We investigated the extent of genetic subdivision in the Australian freshwater fish Pseudomugil signifer (Kner) (Pseudomugilidae) from two drainages in northern Queensland, Australia, using allozyme techniques. The drainages were adjacent and had similar channel patterns each with two major subcatchments coalesced to an estuarine confluence. Analysis of 30 sites across the two drainages revealed that although there was significant genetic variation among sites in both drainages, this was not between the two subcatchments in either case. This result did not support predictions of the stream hierarchy model (SHM), which would predict higher levels of variation among subcatchments than within them, nor did it suggest that estuarine conditions represent a significant barrier to dispersal in this species. More variation was among sites within each subcatchment. Multidimensional scaling plots revealed that, although most sites within a drainage were similar to one another, outlier sites occurred in each drainage, so correlations between genetic distance and geographic distance were weak. We suggest that the distance between sites and the probability of connectivity between sites may better explain the observed distribution of genetic diversity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".