Bibliographic record
Abstract
We grew Thalassiosira weissflogii to steady state over a range of Fe-limiting conditions with nitrate or ammonium as the N source. Nitrate-dependent cells had faster Fe-uptake rates, contained significantly higher intracellular Fe quotas, and grew faster than cells cultivated with NH4+ when Fe was most limiting. Under these conditions, carbon (C) : chlorophyll a ratios and the minimum fluorescence yield per chlorophyll a increased, but N source had no effect on either parameter. The ratio of variable to maximum fluorescence (Fv Fm−1) declined little with Fe limitation m even when T. weissflogii was grown at 25% of its maximum rate (µmax). C:N ratios were higher in nitrate than in ammonium-grown cells and were constant at all Fe levels. Protein was independent of Fe and N, and amino acids were lowest in cells using NO3−. The P content of T. weissflogii (mol P L−1 cell volume) increased by 1.5 times as Fe became most limiting to growth, causing N: P and C: P ratios to decline significantly. The elemental stoichiometry for Fe-limited new production of T. weissflogii (0.25µmax) was thus 70C : 10N : 5.9Si : 1P : 0.00074Fe (by mols) compared with 97C : 14N : 4.7Si : 1P : 0.029Fe for nutrient-replete conditions. Uptake rate ratios of NO3− : PO43− showed the same dependence on Fe as the cellular N: P quotas, decreasing as [Fe] decreased. Iron limitation influenced the elemental composition of this marine diatom and will alter the assimilation ratios of C, N, and P in the high nitrate, low chlorophyll regions of the sea.
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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 | 0.000 | 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 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".