Population Genetics of Bowfins (Amiidae) across the Laurentian Great Lakes
Bibliographic record
Abstract
The Bowfin, Amia calva (Linneaus, 1766), is a common Eastern North American fish and the last extant member of the order Amiiformes. By 1870, thirteen species of bowfin had been described across North America. These species included Amia ocellicauda from Georgian Bay in Lake Huron (Todd, in Richardson, 1836), A.occidentalis from St. Mary’s River in Lake Huron (Dekay, 1842), A. canina from Lake Erie (Cuvier and Valenciennes, 1847) and the first-described bowfin, A. calva, from Charleston, South Carolina. This diversity was condensed down to a single species, A. calva, by Jordan and Evermann in 1896. Since then, this monotypy hypothesis has been generally accepted, but never scientifically validated. In 2014, this hypothesis was challenged when specimens from the Savanah River and Lake Ontario basins were compared morphometrically (Clifford, 2014). Results from this study concluded that there were in fact 2 distinct species. Fish from the Savanah River basin should be referred to as Amia calva and those from Lake Ontario as Amia species incertae sedis. Our study continues the testing of the monotypy hypothesis using molecular biology. Analysis of the barcoding gene Cythochrome Oxidase I is being used to phylogenetically compare specimens collected from Lake Huron, Lake Erie, and the Carolinas. Sanger sequencing of this gene has allowed us to properly align and genetically classify fish from each locality. As a result, we can then begin to delineate potential species and improve taxonomic classification. Data collected from our study is also being used to complement morphometric data and eventually shed light on a subject which has been untouched for almost 120 years.
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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 | 0.001 | 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".