Hydroelectric development and translocation of<i>Galaxias brevipinnis</i>: a cloud at the end of the tunnel?
Bibliographic record
Abstract
Two major drainages of southeastern Australia, the Snowy River and the Murray River, were artificially linked by a major hydroelectric project during the early 20th century. This development diverts Snowy River flow into tributaries of the Murray River via a series of extensive tunnels. In 1990, fish surveys of the upper Murray River system recorded Galaxias brevipinnis, an aggressive migratory species previously unrecorded from the drainage. We used genetic analysis to discriminate between alternative hypotheses for Murray River G. brevipinnis: (i) anthropogenic translocation via the Snowy River diversion or (ii) a previously undiscovered natural population. Landlocked G. brevipinnis from the Murray River (43 fish, eight control region haplotypes) and Snowy River (39 fish, 11 haplotypes) exhibit similar levels of mtDNA diversity, share six haplotypes, and are not significantly differentiated for microsatellite loci (p = 0.0884). Coastal samples exhibit higher haplotypic diversity (40 fish, 20 haplotypes) but share only three haplotypes with Murray River and are significantly differentiated from Murray River samples for microsatellite loci (p = 0.0008). Our data are consistent with the translocation hypothesis but are generally inconsistent with a natural origin for Murray River G. brevipinnis. The suggested human-mediated translocation represents a risk to native fauna.
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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 | 0.001 |
| 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".