Newly discovered deep-branching marine plastid lineages are numerically rare but globally distributed
Bibliographic record
Abstract
Ocean surface warming is resulting in an expansion of stratified, low-nutrient environments, a process referred to as ocean desertification [1]. A challenge for assessing the impact of these changes is the lack of robust baseline information on the biological communities that carry out marine photosynthesis. Phytoplankton perform half of global biological CO 2 uptake, fuel marine food chains, and include diverse eukaryotic algae that have photosynthetic organelles (plastids) acquired through multiple evolutionary events [1–3]. While amassing data from ocean ecosystems for the Baselines Initiative (6,177 near full-length 16S rRNA gene sequences and 9.4 million high-quality 16S V1-V2 amplicons) we identified two deep-branching plastid lineages based on 16S rRNA gene data. The two lineages have global distributions, but do not correspond to known phytoplankton. How the newly discovered phytoplankton lineages contribute to food chains and vertical carbon export to the deep sea remains unknown, but their prevalence in expanding, low nutrient surface waters suggests they will have a role in future oceans.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".