Estimates of net community production from multiple approaches surrounding the spring ice-edge bloom in Baffin Bay
Bibliographic record
Abstract
Measurements of net community production (NCP) provide an upper constraint on the strength of the oceanic biological pump, the dominant mechanism for removing CO2 from the ocean surface and sequestering it at depth. In this investigation, our objectives were to describe the spatial and temporal variability of NCP associated with the spring ice-edge bloom in Baffin Bay and to identify the key environmental drivers controlling its variability. Using data collected between June 9 and July 10, 2016, we estimated NCP based on (1) underway measurements of surface water oxygen to argon ratios (O2:Ar), (2) underway measurements of the partial pressure of CO2, and (3) seasonal nitrate drawdown from discrete samples. These multiple approaches displayed high NCP (up to 5.7 mol C m–2) in eastern Baffin Bay, associated with modified Atlantic waters, and low NCP (<1 mol C m–2) in the presence of Arctic outflow waters in western Baffin Bay. Arctic outflow waters were characterized by low surface salinities and nitrate concentrations, suggesting that high freshwater content may have limited the nutrient availability of these waters. Different integration depths and timescales associated with each NCP approach were exploited to understand the temporal progression and succession of the bloom, revealing that the bloom was initiated under ice up to 15 days prior to ice retreat and that a large portion of NCP in eastern Baffin Bay (potentially up to 70%) was driven by primary production occurring below the surface-mixed layer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".