Dataset: Nitrous oxide cycling in the Western Arctic Ocean from stable isotopic and concentration data during the Seventh Chinese Arctic Research Expedition (CHINARE) (7/19/16 to 9/9/16)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nitrous oxide is a potent greenhouse gas in the troposphere and an ozone-depleting substance in the stratosphere, yet its sources and sinks in the ocean are neither well-quantified nor well understood. Nitrous oxide is both produced and consumed by microbial processes; it is produced by different processes dependent upon the amount of oxygen present locally. High nitrous oxide saturations were recently observed in productive shallow Arctic shelf waters. The primary goal of this dataset is to evaluate nitrous oxide cycling in the Western Arctic Ocean from its concentrations, stable isotopes and isotopomers. The project will use isotopic and isotopomer measurements from both shelf and offshore waters to constrain estimates of nitrous oxide cycling in the Arctic. The data will be used to evaluate 1) the pathways of nitrous oxide production from either nitrification following organic matter decomposition in the water column or coupled nitrification-denitrification in the sediments and 2) how these processes influence nitrous oxide exchanges between the surface layer and the atmosphere. Comparisons of observations at coastal and shelf stations in the Bering and Chukchi seas with those offshore in the Deep Canadian Basin will allow the evaluation of the effects of mixing and long-range transport on geochemical signals. The measurements will also serve as a baseline for future assessment of change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it