Dissolved greenhouse gas measurements in Cambridge Bay, Nunavut, Canada (June/July 2022, June/July 2023)
Bibliographic record
Abstract
Dissolved methane (CH4) and carbon dioxide (CO2) were measured in Cambridge Bay, Nunavut, Canada in ponds and a lake-river-bay continuum during two field seasons in June-July 2022 and June-July 2023. Cambridge Bay experiences a seasonal freeze-thaw cycle; During the winter frozen season, methane and carbon dioxide, naturally released from biological decay and permafrost heaving, become trapped in water bodies under ice. During the spring thaw, questions remain regarding the dynamics and fate of these gases including whether they are ventilated, consumed, or transported. We present a two-year study measuring dissolved greenhouse gas concentrations in the Canadian High Arctic at the Greiner Lake Watershed in Cambridge Bay (Iqaluktuuttiaq), Nunavut during the 2022 and 2023 spring thaws. Measurements of dissolved CH4, CO2, temperature, and salinity were made along a lake-river-bay continuum, including local ponds, using a suite of in situ sensors. CH4 and CO2 were measured using a Los Gatos Research (LGR) dissolved gas extraction unit (DGEU) coupled to a LGR greenhouse gas analyzer (GGA). Instruments were deployed shoreside and with the ChemYak, a remotely operated robotic kayak developed by the Woods Hole Oceanographic Institution (WHOI). This study represents how key technologies, sensors, and targeted sampling campaigns could be established to help us predict future greenhouse gas dynamics in changing Arctic systems.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".