The influence of light on copper‐limited growth of an oceanic diatom,<i>Thalassiosira oceanica</i>(Coscinodiscophyceae)
Bibliographic record
Abstract
Thalassiosira oceanica(CCMP1005) was grown over a range of copper concentrations at saturating and subsaturating irradiance to test the hypothesis that Cu and light were interacting essential resources. Growth was a hyperbolic function of irradiance in Cu‐replete medium (263 fmol Cu′ · L−1) with maximum rates achieved at 200 μmol photons · m−2 · s−1. Lowering the Cu concentration at this irradiance to 30.8 fmol Cu′ · L−1decreased cellular Cu quota by 7‐fold and reduced growth rate by 50%. Copper‐deficient cells had significantly slower (P < 0.0001) rates of maximum, relative photosynthetic electron transport (rETRmax) than Cu‐sufficient cells, consistent with the role of Cu in photosynthesis in this diatom. In low‐Cu medium (30.8 fmol Cu′ · L−1), growth rate was best described as a positive, linear function of irradiance and reached the maximum value measured in Cu‐replete cells when irradiance increased to 400 μmol photons · m−2 · s−1. Thus, at high light, low‐Cu concentration was no longer limiting to growth: Cu concentration and light interacted strongly to affect growth rate ofT. oceanica(P < 0.0001). RelativeETRmaxand Cu quota of cells grown at low Cu also increased at 400 μmol photons · m−2 · s−1to levels measured in Cu‐replete cells. Steady‐state uptake rates of Cu‐deficient and sufficient cells were light‐dependent, suggesting that faster growth ofT. oceanicaunder high light and low Cu was a result of light‐stimulated Cu uptake.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".