GEOTRACES: Multi-tracer investigation of the effect of climate change on nutrient and carbon cycles in the Arctic Ocean
Bibliographic record
Abstract
Our sampling program took place from August 27, 2009 through September 12, 2009. It was part of Leg 3a of the 2009 CCGS Amundsen Expedition in the Arctic Ocean (ArcticNet 0903). Sampling started in the Mackenzie River delta and continued into the Beaufort Sea (Shelf, slope and deep Canada Basin). Various measurements (temperature, salinity, nutrients, alkalinity, pH, primary production, bacterial production) and sampling (seawater, marine particles) were conducted at 10 stations. Underway measurements (temperature, salinity, trace gases) and sampling (marine particles) were also conducted along the cruise track. Sampling tools on stations were the ship's CTD/rosette (ArcticNet), a Trace-Metal CTD/rosette system (UVic / UBC) and large volume in-situ pumps (UBC). We conducted measurements and collected samples to document a suite of key physical (temperature, salinity, ice cover, light penetration), chemical (nutrients, trace metals, trace gases, radioisotopes, stable isotopes) and biological (phytoplankton and microbial assemblages, primary and microbial productivity, trace metal phytoplankton quotas) parameters in relation to proximity to the Mackenzie River delta, seafloor bathymetry and ice cover to elucidate the processes influencing phytoplankton growth and carbon cycling in the Arctic Ocean. In particular, we collected samples to study the processes which supply and remove trace metals, nutrients and carbon to and from the upper ocean, and conducted ship-board experiments to study how biological productivity is affected by various chemical and physical conditions. Through a combination of on-board measurements, experiments and subsequent laboratory analysis, our research program aims at: (i) documenting the pathways of addition, removal and cycling of key trace elements which act as biological micronutrients or tracers of carbon and nutrient cycles in the Arctic Ocean; (ii) elucidating the potential effects of changing ice cover and river discharge on productivity, carbon sequestration and trace gas emission in the Arctic Ocean; (iii) developing chemical tracers to establish a historical sedimentary record of Arctic Ocean productivity in relation to long term natural climate change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".