How do marine diatoms fix 10 billion tonnes of inorganic carbon per year?
Bibliographic record
Abstract
Diatoms are responsible for at least a quarter of inorganic carbon fixed each year in the ocean. Despite very considerable research over the last 30 years, there are still a number of fundamental unresolved aspects of inorganic carbon assimilation by marine diatoms. It is not clear how the carbon-concentrating mechanism functions and whether it is based on the direct acquisition of inorganic carbon or on a C4pathway, or a combination of both. Although evidence for the operation of a C4pathway is accumulating, the role(s) of the enzyme(s) responsible for "C3+ C1" inorganic carbon assimilation in the light and dark are still matters of controversy. In this review, we discuss whether diatoms possess the enzymic and structural components necessary for a C4-type CO2-concentrating mechanism. These are compared and contrasted with other C4systems, both single-celled and those in terrestrial plants, which are based on Kranz anatomy. New data are presented on expression of genes that might be involved in C4photosynthesis, including phosphoenolpyruvate carboxylase and phosphoenolpyruvate carboxykinase.Key words: CO2-concentrating mechanism, C4photosynthesis, marine diatoms, phosphoenolpyruvate carboxylase, phosphoenolpyruvate carboxykinase.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".