Design of a molecular assay to differentiate ‘white’ from ‘common’ threespine stickleback (Gasterosteus aculeatus) ecotypes
Bibliographic record
Abstract
The 'White' Threespine Stickleback is a form of stickleback endemic to Nova Scotia, Canada, which exists sympatrically with the 'common' marine Threespine Stickleback.These fish differ in both morphology and behaviour.White stickleback change colour to an iridescent white during the breeding season rather than blue like the commons.Common males also care for eggs while they are in their nests whereas white males remove eggs from their nests and disperse them throughout the surrounding algae.Aside from male breeding colouration there are no known morphological traits that clearly differentiate white from common ecotypes.Therefore, an effective identification method is necessary to classify females, juvenile males, and mature males outside of the breeding season to study the mechanisms underlying adaptive divergence in colouration and parental care.White and common stickleback do form genetically distinct groups and in this thesis I attempted to develop a molecular assay to identify the fish by using previously identified regions of the stickleback genome with high differentiation between the two ecotypes.I designed primer sets to amplify microsatellite markers from these 'outlier' regions and analyzed allele frequencies of three loci with a discriminant analysis of principal components.I found that the use of only three markers was insufficient to differentiate the ecotypes, so the addition of other markers will be needed to design a successful assay.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".