A comparison of two DNA barcode markers for species discrimination in the red algal family Kallymeniaceae (Gigartinales, Florideophyceae), with a description of <i>Euthora timburtonii</i> sp. nov.
Bibliographic record
Abstract
Accurate identification of many red algae to the species level using only morphological characters can be difficult. The emerging field of “molecular-assisted alpha taxonomy” can greatly alleviate this issue. In this approach, a large number of specimens are sequenced for a standard DNA marker as a first step to genetic species assignment, followed by detailed morphological observations. Regions of both the mitochondrial cytochrome c oxidase I gene (COI-5P) and the plastid 23S rRNA gene (UPA) have been proposed as DNA barcode markers to accomplish this task. We compared the utility of each marker as a species identification tool using members of the marine red algal family Kallymeniaceae from British Columbia, Canada. Our results indicate that COI-5P is a more sensitive marker for delimiting species, but that it can be difficult to acquire clean amplification products for many isolates of Kallymeniaceae, owing to biological contamination. This problem can be overcome by using specific primers. UPA, on the other hand, has universal primers that work in diverse lineages (e.g., red, brown, and green algae), but lower interspecific sequence variation, which has the potential to underestimate species diversity, although this was not observed in our study. During our survey, we uncovered a new species of the Kallymeniaceae, Euthora timburtonii Clarkston et G.W. Saunders sp. nov., which we describe here.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".