Genetic structure and congeneric range overlap among sharpnose sharks (genus <i>Rhizoprionodon</i>) in the Northwest Atlantic Ocean
Bibliographic record
Abstract
Sharpnose sharks (genus Rhizoprionodon) experience extensive fishing pressure throughout their ranges in the Atlantic Ocean. As such, it is important to understand the degree to which intraspecific populations interact across a spatial gradient. The Atlantic sharpnose shark (Rhizoprionodon terraenovae) and Caribbean sharpnose shark (Rhizoprionodon porosus) share a similar appearance and spatial presence within the Gulf of Mexico, though until recently only R. terraenovae was observed north of the Bahamas. We assessed the population structure of R. terraenovae using the mitochondrial control region (650 bp). Our results indicate significant genetic structure (FST = 0.049, P < 0.001; ΦST = 0.017, P = 0.008) between the Gulf of Mexico and the rest of the Atlantic. In addition, we observed R. porosus outside their known range, in South Carolina, Virginia, and northern Florida. Given the overlapping range with R. terraenovae, we assessed the potential for congeneric hybridization with the addition of the nuclear ribosomal internal transcribed spacer 2 gene (1260 bp). Results designate these specimens to be true R. porosus specimens, indicating the need for reevaluation of this species’ range.
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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 | 0.000 |
| 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".