Characterisation of pyrenoid components in the diatom Thalassiosira pseudonana
Bibliographic record
Abstract
Eukaryotic algae are responsible for approximately one-third of global carbon fixation.To maximise photosynthetic efficiency, algae have evolved biophysical carbon concentrating mechanisms (CCMs), concentrating inorganic carbon (Ci) to saturate Ribulose-1,5-bisphosphate carboxylase-oxygenase (Rubisco) with CO2.Central to the algal CCM is the pyrenoid, a dynamic, Rubisco-containing organelle located in the chloroplast.Diatoms, an algal group with CCMs, are found in freshwater and ocean environments.They are important primary producers responsible for up to 20% of global carbon fixation.Current understanding of the diatom CCM is incomplete with key pyrenoid components unknown or uncharacterized.These components include linker proteins which bind Rubisco to drive pyrenoid formation, carbonic anhydrases (CAs) which release CO2 for fixation by Rubisco and Shell proteins hypothesized to prevent CO2 loss from the pyrenoid.This study uses bioinformatic techniques to investigate linker proteins, CAs and Shell proteins, particularly focusing on the model diatom Thalassiosira pseudonana.A novel combination of structural and phylogenetic analysis gives insight into the complexities of CCM component evolution between ecologically relevant algal lineages.
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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 | 0.000 | 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 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".