Acquiring DNA sequence data from dried archival red algae (Florideophyceae) for the purpose of applying available names to contemporary genetic species: a critical assessment
Bibliographic record
Abstract
Two DNA extraction protocols and nine variations of advocated DNA barcode markers (nuclear LSU D2/D3, ITS1, ITS2, mitochondrial COI-5P, plastid rbcL, UPA) were assessed for their abilities to yield species-level resolution from archival collections of red algae. With the exception of LSU D2/D3, all markers trialed displayed the potential to resolve red algal species. However, shortened COI-5P (COIms) and ITS (ITS2r) markers displayed four to five times the intrageneric divergence of shortened plastid markers and are preferred for their resolving power. For recent archival samples (4–11 years), COIms, ITS2r, and UPA displayed >90% amplification success. However, success rates declined rapidly as samples ranging in age from ca. 45–180 years old were tested. Further, contamination was a serious concern in reamplifications (partially nested PCR), especially for markers using universal primers (e.g., UPA) and for trials that employed the best extraction procedure, i.e., the better an extraction protocol is at isolating small DNA fragments from archival material, the better it is at acquiring small contaminating fragments from the laboratory — an intuitive and unfortunate reality. The ramifications of our results for ongoing attempts to extract DNA from archival red algal collections using PCR-based protocols is discussed along with recommendations to improve the likelihood of authentic outcomes.
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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 | 0.024 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".