Applying DNA barcoding to red macroalgae: a preliminary appraisal holds promise for future applications
Bibliographic record
Abstract
Marine macroalgae, especially the Rhodophyta, can be notoriously difficult to identify owing to their relatively simple morphology and anatomy, convergence, rampant phenotypic plasticity, and alternation of heteromorphic generations. It is thus not surprising that algal systematists have come to rely heavily on genetic tools for molecular assisted alpha taxonomy. Unfortunately the number of suitable marker systems in the three available genomes is enormous and, although most workers have settled on one of three or four models, the lack of an accepted standard hinders the comparison of results between laboratories. The advantages of a standard system are obvious for practical purposes of species discovery and identification; as well, compliance with a universal marker, such as cox1 being developed under the label 'DNA barcode', would allow algal systematists to benefit from the rapidly emerging technologies. Novel primers were developed for red algae to PCR amplify and sequence the 5' cox1 'barcode' region and were used to assess three known species-complex questions: (i) Mazzaella species in the Northeast Pacific; (ii) species of the genera Dilsea and Neodilsea in the Northeast Pacific; and (iii) Asteromenia peltata from three oceans. These models were selected because they have all caused confusion with regards to species number, distribution, and identification in the field, and because they have all been studied with molecular tools. In all cases the DNA barcode resolved accurately and unequivocally species identities and, with the enhanced sampling here, turned up a variety of novel observations in need of further taxonomic investigation.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".