The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions
Bibliographic record
Abstract
Abstract. High-latitude terrestrial ecosystems are key components in the global carbon (C) cycle. Estimates of global soil organic carbon (SOC), however, do not include updated estimates of SOC storage in permafrost-affected soils or representation of the unique pedogenic processes that affect these soils. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify the SOC stocks in the circumpolar permafrost region (18.7 × 106 km2). The NCSCD is a polygon-based digital database compiled from harmonized regional soil classification maps in which data on soil order coverage have been linked to pedon data (n = 1778) from the northern permafrost regions to calculate SOC content and mass. In addition, new gridded datasets at different spatial resolutions have been generated to facilitate research applications using the NCSCD (standard raster formats for use in geographic information systems and Network Common Data Form files common for applications in numerical models). This paper describes the compilation of the NCSCD spatial framework, the soil sampling and soil analytical procedures used to derive SOC content in pedons from North America and Eurasia and the formatting of the digital files that are available online. The potential applications and limitations of the NCSCD in spatial analyses are also discussed. The database has the doi:10.5879/ecds/00000001. An open access data portal with all the described GIS-datasets is available online at: http://www.bbcc.su.se/data/ncscd/.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".