Bibliographic record
Abstract
Abstract. We compare primary productivity estimates based on different photosynthetic ‘currencies’ (electrons, O2 and carbon) collected from the dynamic coastal upwelling waters of the California Current. Fast Repetition Rate Fluorometry and O2/N2 measurements were used to collect high-resolution underway estimates of photosynthetic electron transport rates and net community productivity, respectively, alongside on-station 14C uptake experiments to measure gross carbon fixation rates. Our survey captured two upwelling filaments at Cape Blanco and Cape Mendocino with distinct biogeochemical signatures and iron availabilities, enabling us to examine photosynthetic processes along a natural iron gradient. Significant differences in photo-physiology, cell sizes, Si:NO3- draw-down ratios, and molecular markers of Fe-stress indicated that phytoplankton assemblages near Cape Mendocino were Fe-stressed, while those near Cape Blanco were Fe-replete. Upwelling of O2-poor deep water to the surface complicated O2-based net community productivity estimates, but we were able to correct for these vertical mixing effects using continuous [N2O] surface measurements and depth-profiles of ∂[O2]∂[N2O]. Vertical mixing corrections were strongly correlated to sea surface temperature, which serves as an N2O-independent proxy for upwelling. Following vertical mixing corrections, all three productivity estimates reflected trends in Fe-stress physiology, indicating greater productivity near Cape Blanco compared to Cape Mendocino. For all assemblages, carbon fixation varied as a hyperbolic function of electron transport rates, but the derived parameters of this relationship were highly variable and significantly correlated with physiological indicators of Fe-stress (σPSII, FV/FM, Si:NO3- and diatom-specific PSI gene expression), suggesting that iron availability influenced the coupling between photosynthetic electron transport and subsequent carbon fixation. Net community productivity showed strong coherence with daily-integrated photosynthetic electron transport rates across the entire cruise track, with no apparent relationship with Fe-stress. This result suggests that fluorescence-based estimates of gross photochemistry are still a good indicator for bulk primary productivity, even if Fe-limitation influences the stoichiometric relationship between productivity currencies.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.017 | 0.009 |
| Insufficient payload (model declined to judge) | 0.500 | 0.375 |
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".