An examination of Crassostrea virginica nuclear DNA variation along the North Carolina coast
Bibliographic record
Abstract
Inhabiting coastal waters from eastern Canada to the Gulf of Mexico, the eastern oyster is subjected to a wide range of temperature and salinity regimes, thus providing an interesting opportunity to study population structure. Prior studies have examined phenotypic as well as DNA differences along this range. A previous mtDNA population survey of Crassostrea virginica within Pamlico Sound utilizing a single 16s polymorphism diagnostic for North Atlantic / South Atlantic haplotypes revealed an ~110 km cline along the North Carolina coast. Using 4 microsatellite loci, 3 SNPs and 1 scnDNA RFLP, I have surveyed eight oyster populations within and outside the Pamlico Sound in an effort to corroborate the population structure found in the mitochondrial genome. Three microsatellite loci were out of HWE across populations vs. only 1 population for one SNP loci, and it seems likely that those microsatellite loci were plagued with null alleles. Microsatellite exact tests show some significant differences within the Pamlico Sound, mostly in comparisons involving the Stumpy Point population. A combined SNP/RFLP analysis did reveal significant differences among populations, though most of this can be accounted for by inclusion of a population from Maryland. The clinal structure seen in the mitochondrial genome is not reflected in the nuclear genome within the Pamlico Sound.
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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".