Synthesized double stranded gene fragments are not suitable for qPCR endogenous control spike-ins
Bibliographic record
Abstract
OBJECTIVE: Quality control standards are paramount for eDNA methods to gain widespread acceptance. In targeted eDNA studies, there are three main stages: sample collection, DNA extraction, and amplification via PCR. During this process, positive controls that ensure procedural success and validate negative results are typically included only in the final PCR amplification stage of the workflow. To address this issue, we explored the possibility of using synthetic dsDNA gene fragment spike-ins as endogenous controls to monitor the success of the sample collection and DNA extraction phases of the workflow. We hypothesised that short fragments of assay-specific dsDNA would be suitable for an endogenous control to monitor method success. To test this, we spiked dsDNA into two matrices, river water and TE buffer, where we then filtered and extracted each matrix and assessed the recovery of the spike-in. RESULTS: Our findings concluded that common eDNA collection and extraction methodologies do not consistently capture and isolate dsDNA fragments as we were unable to recover any of the dsDNA spike-ins. Thus, such fragments are unsuitable for a pre-extraction endogenous control. Further, this suggests that similar size dsDNA fragments in the environment may be missed by filtration-based eDNA studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".