An evaluation of rbcL, tufA, UPA, LSU and ITS as DNA barcode markers for the marine green macroalgae
Bibliographic record
Abstract
T he universality and species discriminatory power of the plastid rubisco large subunit (rbcL) (considering 5' and 3' fragments independently), elongation factor tufA ,a nd universal amplicon (UPA), and the nuclear D2/D3 region of the large ribosomal subunit (LSU) and the internal transcribed spacer of the ribosomal cistron (ITS) were evaluated for their utility as DNA barcode markers for green macroalgae. Excepting low success for ITS, all of these markers failed for the Cladophoraceae. For the remaining taxa, the 3' region of the rbc L( rbcL-3P) and tufA had the largest barcode gaps (difference between maximum intra- and minimum inter-specific divergence). Unfortunately, moderate amplification success (80 %e xcluding Cladophoracae) caused, at least in part, by the presence of introns within the rbcL-3P for some taxa reduced the utility of this marker as au niversal barcode system. The tufA marker, on the other hand, had strong amplification success (95% excluding the Cladophoraceae) and no introns were uncovered. We thus recommend that tufA be adopted as the standard marker for the routine barcoding of green marine macroalgae (excluding the Cladophoraceae). During this survey we discovered cryptic species in Acrosiphonia, Monostroma ,a nd Ulva indicating that significant taxonomic work remains for green macroalgae. Chlorophyta /D NA barcoding /g reen algae /I TS /L SU / rbc L/ tufA /U P
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".