Effects of silicate resupply to silicate‐deprived <scp><i>T</i></scp><i>halassiosira weissflogii</i> (<scp>B</scp>acillariophyceae) in stationary or senescent phase: short‐term patterns of growth and cell death
Bibliographic record
Abstract
The ability of nutrient-deprived phytoplankton to recover in the short term when nutrients are resupplied has been studied for nitrogen and phosphorus, but the case for silicate (Si) is poorly understood. Si-limited Thalassiosira weissflogii (Grunow) Fryxell et Hasle (grown in batch culture) was harvested in stationary phase (when cell numbers stopped increasing ~2 d after Si depletion) and senescence (when cell numbers declined ~4 d after Si depletion) and Si was resupplied at different concentrations (from 0 to 100 μM). Cell numbers, proportion of dead cells, variable fluorescence emissions (Fv /Fm ), and activities of proteases were measured during Si depletion and for 24 h after Si resupply. As Si was depleted, the specific growth rate declined, dead cells increased from ~2% in log phase, to ~25% in stationary phase to over 35% in senescence, and activities of proteases associated with cell death increased several-fold. Concentration-dependent recovery of growth rate was seen after 24 h for cultures resupplied with Si in stationary phase but not in senescence. However, resupply of Si at 100 μM to stationary phase cultures alone increased protease activity to nearly the levels seen in senescence. Differences in the responses to Si resupply suggest that the ability and time to recover from Si depletion depend not only on the growth phase but also on the concentration resupplied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".