Temporal Genetic Similarity Among Year-Classes of the Pacific Geoduck Clam (<i>Panopea generosa</i>Gould 1850): A Species Exhibiting Spatial Genetic Patchiness
Bibliographic record
Abstract
A previous study revealed genetic differences among collections of the commercially exploited geoduck clam (Panopea generosa) in Puget Sound, WA, but this heterogeneity did not follow an isolation-by-distance model. In this study, we investigated whether these differences were ephemeral or stable and tested predictions of the sweepstakes recruitment hypothesis, in which individuals show a high variance in reproductive success. We genotyped 11 allozyme and 7 microsatellite loci in 2,021 geoducks from 2 sites in Puget Sound and aged individuals by counting annuli in thin-section chondrophores under light microscopy. Genotypic data were then collated by year-class to test predictions of the sweepstakes recruitment hypothesis with allele count rarefaction, year-class relatedness, and 3 estimators of efective population size (Ne) using temporal shifts in allele frequencies. Although estimates of Ne were similar among year-classes, spatial shifts in allele frequencies and year-class strengths were detected among stations at 1 site, indicating that patchy settlement may be the result of an interaction between larval behavior during dispersal and hydrology.
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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".