SGER: Investigation of Potential Co-Introduction of Fucus serratus and Littorina littorea to North America in 1800s
Bibliographic record
Abstract
This research will apply new approaches and expertise to understanding the probable invasion of North American intertidal zones by the herbivorous snail Littorina littorea in the 1800s. The investigator developed the following hypothesis during her recent analyses of late 1700s to mid-1800s shipping records: Fucus serratus and Littorina littorea were co-introduced into North America from Britain via the dumping of intertidal rock ballast in ships arriving at Pictou Harbor during the massive emigration of nearly 40,000 Scots (and some Irish and English) in the late 1700s-mid-1800s. This hypothesis will be tested using innovative molecular techniques (i.e., assay of nuclear and mitochondrial loci with primers that have already been developed for population genetic and phylogeographic studies in both species). Snails and algae will be collected and screened from Pictou (Canada) and 3-4 of the best candidate sites from Britain, based on the frequency of arrivals of ships from different British ports near the time of the putative introductions. The investigator will attempt to determine whether genotypes have remained stable over time (mid-1800s compared to today) in Pictou with herbarium material of F. serratus from the 1800s. The broader impacts include: demonstrating that Pictou Harbor was an epicenter for marine invasions in the last century. This, in turn, should lead to discoveries of other co-introduced species and confirm and extend our theoretical understanding of the trajectory of marine invasions based on different life histories and dispersal strategies of the species (e.g., L. littorea produces larvae; F. serratus produces rapidly attaching zygotes). The proposed SGER should lead to a full, collaborative proposal to pursue the co-introduction and broader multi-species invasion questions within a year.
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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 | 0.001 | 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".