Development and standardization of disomic microsatellite markers for lake sturgeon genetic studies
Bibliographic record
Abstract
Lake sturgeon (Acipenser fulvescens) are of conservation concern in North America. To facilitate the recovery of this fish species, an understanding of their population genetic structure is necessary to develop and implement spatially and temporally appropriate management actions. Until recently, few genetic data using nuclear loci have been collected, primarily due to the paucity of suitable genetic markers because most microsatellite loci in lake sturgeon appeared to be tetrasomic. The authors identified nine microsatellite loci (from 254 examined) that were putative polymorphic disomic loci and tested their conformance to a disomic mode of inheritance using three lake sturgeon families. The objectives of the study were to: (i) confirm the disomic status of the nine loci through inheritance testing, and (ii) standardize the genetic markers among participating laboratories. At all nine loci, disomic inheritance were confirmed, and all nine loci segregated independently in the 26 of 36 loci pairs possible to test. One of the nine loci showed non-Mendelian segregation, possibly due to meiotic drive and/or selection. Three progeny had peak patterns inconsistent with disomy at one or more loci. The nine loci when combined with four microsatellite loci previously confirmed in other studies as disomic in lake sturgeon now yield a suite of 13 microsatellite markers. These 13 markers have been standardized among four other laboratories to facilitate building an inter-laboratory genetic database for lake sturgeon.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".