Genetic Analysis and Telemetry Study of Migration Habits of the Endangered Atlantic Sturgeon
Bibliographic record
Abstract
Atlantic sturgeon are a long-lived anadromous fish that ranged from Labrador, Canada to Florida, US. Due to overharvest in the late 1800’s and 1900’s, Atlantic sturgeon populations across the coast experienced a dramatic population crash. Recovery of this species has faced challenges due to anthropogenic threats, such as vessel strikes, bycatch, and habitat degradation. In 2012, Atlantic sturgeon were added to the United States Endangered Species Act (ESA). Under the ESA, populations were listed as five distinct population segments (DPS), reflecting their geographic arrangement and genetic structure: Gulf of Maine DPS (threatened), New York Bight DPS (endangered), Chesapeake DPS (endangered), Carolina DPS (endangered), and South Atlantic DPS (endangered). As sub-adults and adults, Atlantic sturgeon migrate along the eastern coast of the United States and into Canada, temporarily inhabiting marine, estuarine, and riverine habitats. These migrations often lead to the formation of mixed-stock aggregations, with individuals from different populations cooccurring in space and time. Genetic assignment testing was used to relate individuals sampled in the Atlantic Ocean Delaware to their natal population. In this aggregation, individual sturgeon from each of the five DPS were detected. Next, we used telemetry data from the assigned Atlantic sturgeon to compare the upriver movement patterns between natal and non-natal fish into the Hudson and Delaware Rivers. Statistically significant differences were found between the upriver movement patterns of natal and non-natal Atlantic sturgeon in both rivers (Hudson, p=0.016; Delaware, p=1.56x10-11). Differences in upriver travel were also compared between males and females, where males tended to travel further upriver than females for both natal and non-natal individuals (p.05).
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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 | 0.001 | 0.001 |
| 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".