DISTRIBUTION, PHYLOGENY, AND GROWTH OF COLD‐ADAPTED PICOPRASINOPHYTES IN ARCTIC SEAS<sup>1</sup>
Bibliographic record
Abstract
Our pigment analyses from a year‐long study in the coastal Beaufort Sea in the western Canadian Arctic showed the continuous prevalence of eukaryotic picoplankton in the green algal class Prasinophyceae. Microscopic analyses revealed that the most abundant photosynthetic cell types were Micromonas ‐like picoprasinophytes that persisted throughout winter darkness and then maintained steady exponential growth from late winter to early summer. A Micromonas (CCMP2099) isolated from an Arctic polynya (North Water Polynya between Ellesmere Island and Greenland), an ice‐free section, grew optimally at 6°C–8°C, with light saturation at or below 10 μmol photons·m −2 ·s −1 at 0°C. The 18S rDNA analyses of this isolate and environmental DNA clone libraries from diverse sites across the Arctic Basin indicate that this single psychrophilic Micromonas ecotype has a pan‐Arctic distribution. The 18S rDNA from two other picoprasinophyte genera was also found in our pan‐Arctic clone libraries: Bathycoccus and Mantoniella . The Arctic Micromonas differed from genotypes elsewhere in the World Ocean, implying that the Arctic Basin is a marine microbial province containing endemic species, consistent with the biogeography of its macroorganisms. The prevalence of obligate low‐temperature, shade‐adapted species in the phytoplankton indicates that the lower food web of the Arctic Ocean is vulnerable to ongoing climate change in the region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".