Statolith Chemical Analysis as a Means of Identifying Stream Origins of Lampreys in Lake Huron
Bibliographic record
Abstract
Management of the sea lamprey Petromyzon marinus in the North American Great Lakes would be facilitated by a technique that linked parasitic-phase adults to their natal rivers. We hypothesized that the elemental composition of statoliths in ammocoetes differed among river systems and could be used as a natural tag in the adults. To test this hypothesis we compared the composition of statoliths from three rivers in Michigan's lower peninsula with those from two sites in the St. Marys River, a major spawning area for lampreys in Lake Huron. Probe microanalysis indicated that five elements could be measured accurately and reliably in the statoliths and differed significantly among sites. Strontium and rubidium differences among specimens alone were sufficient to correctly assign most specimens to their natal rivers and almost perfectly distinguished between specimens from the St. Marys River and those from the drainages of Michigan's lower peninsula. The limited environmental data available suggest that these differences reflect the ambient concentrations of Sr and Rb in the river systems and, in particular, reflect regional differences in the geochemistry of the Canadian Shield and Michigan Basin. These regional signatures are likely to provide a means of assessing gross population structure of lampreys in the Great Lakes; however, the geographic resolution achievable by means of statolith analysis may be limited to regions rather than specific rivers.
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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 | 0.000 |
| 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) | 0.000 | 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".