Bibliographic record
Abstract
Abstract. Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie Delta region of northwestern Canada, coupled with increases in river discharge and coastal erosion, trigger the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing, well-established, and its rate is accelerating, the fate of the newly-mobilized organic matter, as it transits from the watershed through the delta and into the marine system, remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice break-up in summer, as well as anterior to the freeze-up period in fall. To capture the fluvial-marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms: helicopters, snowmobiles and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC, DOC), and chromophoric dissolved organic matter (CDOM), as well as a suite of physical, chemical and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, colored dissolved organic matter absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in Juhls et al. 2021. https://doi.pangaea.de/10.1594/PANGAEA.937587.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.024 | 0.010 |
| Insufficient payload (model declined to judge) | 0.305 | 0.241 |
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".