A DNA barcode examination of the red algal family Dumontiaceae in Canadian waters reveals substantial cryptic species diversity. 1. The foliose <i>Dilsea</i>–<i>Neodilsea</i> complex and <i>Weeksia</i>This paper is one of a selection of papers published in the Special Issue on Systematics Research.
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
The field of DNA barcoding is working towards generating a genetic system for the quick and accurate identification of eukaryotic species. For the more systematic minded, however, DNA barcoding offers a new approach towards screening and uniting large numbers of biological specimens in genetic groups as a first step towards assigning them to species and genera in an approach best termed “molecular-assisted alpha taxonomy”. This approach is particularly amenable in organisms with simple morphologies, a propensity for convergence, extensive phenotypic plasticity, and life histories with an alternation of heteromorphic generations. It is hard to imagine a group of organisms better defined by all of these traits than the marine macroalgae. In an effort to assess the utility of the DNA barcode (COI-5′) for testing the current concepts of biodiversity of marine macroalgae in Canada, a study to assess species diversity in the red algal family, Dumontiaceae, was initiated. Through this work I confirm the presence in Canadian waters of Dilsea californica (J. Agardh) Kuntze, Dilsea integra (Kjellman) Rosenvinge, and Neodilsea borealis (I.A. Abbott) Lindstrom of the Dilsea–Neodilsea complex, and Weeksia coccinea (Harvey) Lindstrom for the genus Weeksia . However, our work has uncovered two additional species of the former complex, Dilsea lindstromiae Saunders sp. nov. and Dilsea pygmaea (Setchell) Setchell, and an additional species of the latter, Weeksia reticulata Setchell, effectively doubling representation of these foliose dumontiacean genera in Canadian waters.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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