Acquiring DNA sequence data from dried archival red algae (Florideophyceae) for the purpose of applying available names to contemporary genetic species: a critical assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it