Precision and accuracy in fluorescent short tandem repeat DNA typing: Assessment of benefits imparted by the use of allelic ladders with the AmpF<i>l</i>STR®Profiler Plus™ kit
Bibliographic record
Abstract
Base-calling precision of short tandem repeat (STR) allelic bands on dynamic slab-gel electrophoresis systems was evaluated. Data was collected from over 6000 population database allele peaks generated from 468 population database samples amplified with the AmpF/STR Profiler Plus (PP) kit and electrophoresed on ABD 377 DNA sequencers. Precision was measured by way of standard deviations and was shown to be essentially the same, whether using fixed or floating bin genotyping. However, the allelic ladders have proven more sensitive to electrophoretic variations than database samples, which have caused some floating bins of D18S51 to shift on occasion. This observation prompted the investigation of polyacrylamide gel formulations in order to stabilize allelic ladder migration. The results demonstrate that, although alleles comprised in allelic ladders and questioned samples run on the same gel should migrate in an identical manner, this premise needs to be verified for any given electrophoresis platform and gel formulation. We show that the compilation of base-calling data is a very informative and useful tool for assessing the performance stability of dynamic gel electrophoresis systems, stability on which depends genotyping result quality.
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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 | 0.020 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".