Impacts of water depth, sediment pigment concentration, and benthic macrofaunal biomass on sediment oxygen demand in the western Arctic Ocean
Bibliographic record
Abstract
We investigated the impacts of water depth, sediment pigment concentration, and benthic macrofaunal biomass on sediment oxygen demand (SOD) during three cruises to the western Arctic Ocean. SOD values were similar to those of most studies from the Arctic and ranged from a high of 20.68 mmol O2·m2·day1 at a shallow shelf station to a low of 0.29 mmol O2·m2·day1 at the deepest basin station (3648 m). SOD was significantly greater at shallow sites (<500 m; mean = 7.39 mmol O2·m2·day1; standard deviation (SD) = ±5.38) than at deep sites (>500 m; mean = 1.39 mmol O2·m2·day1; SD = ±0.96). As hypothesized, SOD was negatively correlated with water depth and positively correlated with both surface-sediment pigment concentration and macrofaunal biomass, with macrofaunal biomass explaining approximately 74% of the variability in SOD. We propose that higher macrofauna-normalized respiration rates (i.e., SOD divided by macrofaunal biomass) in deep water indicate that microbialmeiofaunal respiration predominates in deep versus shallow water. Finally, deeper stations associated with Barrow Canyon had SODs, benthic macrofaunal biomass, and surface-sediment pigment concentrations that were similar to those of shallower shelf locations, suggesting down-canyon transport of organic material.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".