First attempt to validate multiplex PCR with sex markers SSM4 and ALLWSex2 in long-term stored blood samples of eastern North American shortnose sturgeon ( <i>Acipenser brevirostrum</i> )
Bibliographic record
Abstract
Abstract Sex-specific information is crucial for sturgeon culture, conservation, and fisheries management. However, identifying the sex of sturgeon is difficult, especially for immature individuals. Two recent studies identified two female-specific loci (AllWSex2 and SSM4) that are conserved among many Acipenserid species, but they have not been validated for all species within this family. The objectives of this study were to 1) determine whether SSM4 can be used to sex shortnose sturgeon; 2) develop and test a multiplex PCR technique using both ALLWSex2 and SSM4 for sexing shortnose sturgeon; 3) determine if long-term storage of blood samples can be used to sex shortnose sturgeon; and 4) test the effect of storage temperature on DNA degradation. DNA was extracted from frozen RBC samples from 36 fish which had previously been sexed. A multiplex PCR was set up using three pairs of primers: AllWSex2 and SSM4, as female-specific loci, and mtDNA as an internal control which were all run on a 2 % agarose gel. AllWSex2 and SSM4 allowed for perfect discrimination of sex. While there was DNA degradation, as a result of long-term storage and temperature, the signal was still strong enough after 8 years of cold storage to delineate sex. This suggests that researchers now have the ability to reexamine archived/frozen samples to determine sex of their fish.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".