Effects of iron on the growth and minimal fluorescence yield of three marine <i>Synechococcus</i> strains (Cyanophyceae)
Bibliographic record
Abstract
SUMMARY Two coastal Synechococcus stains PCC 7002 and CC9311 and one oceanic strain WH8102 were cultured with 4–1000 nM Fe in Aquil medium. Compared with those under iron‐replete conditions, their growth rates were significantly decreased by 59% for WH8102 at 15 nM Fe, by 37% for CC9311 at 15 nM Fe and by 57% for PCC 7002 at 4 nM Fe. Among these three strains, PCC 7002 was the most tolerant to iron limitation while WH8102 was the most sensitive to iron limitation. For each strain under the same iron concentration, the growth rates calculated from the minimal fluorescence yield and cell concentration showed no significant difference. The linear correlation was established between the minimal fluorescence yield and cell concentration although the minimal fluorescence yield per cell varied depending on the strains and iron levels. Under iron‐replete conditions, the minimal fluorescence yield per cell was 100‐fold higher for the phycoerythrin‐lacking strain PCC 7002 than two phycoerythrin‐containing strains WH8102 and CC9311. Under iron‐deplete conditions, it was increased respectively by 128% and 7% for WH8102 and CC9311 but was decreased by 30% for PCC 7002. Furthermore, the minimal fluorescence yield per cell for PCC 7002 and CC9311 showed little difference throughout the light and dark diel cycle. However, it was significantly higher for WH8102 in the daytime than in the dark.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 | 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 teacher head, 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".