Updates to the Marine Algal Flora of the Boulder Patch in the Beaufort Sea off Northern Alaska as Revealed by DNA Barcoding + Supplementary Appendix 1 (See Article Tools)
Bibliographic record
Abstract
Since its discovery four decades ago, the Boulder Patch kelp bed community in the Beaufort Sea has been an important site for long-term ecological studies in northern Arctic Alaska. Given the difficulties associated with identifying species of marine algae on the basis of morphology, we sought to DNA barcode a portion of the flora from the area and update a recently published species list. Genetic data were generated for 20 species in the area. Fifty-five percent of the barcoded flora confirmed the morphological species identifications. Five barcoded species revealed what are likely misapplied names to the Boulder Patch flora; the updated names include Ahnfeltia borealis, Phycodrys fimbriata, Pylaiella washingtoniensis, Rhodomela lycopodioides f. flagellaris, and Ulva prolifera. The remaining four species require taxonomic work and possibly represent new records for the Boulder Patch. Our observations indicate that we need considerably more research to understand marine macroalgal biodiversity in the Arctic. Supplementing Arctic species lists using genetic data will be essential in establishing an accurate and reliable baseline for monitoring changes in ecosystem biodiversity driven by long-term changes in regional climate.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".