Synthesis of Winter In Situ Soil CO2 Flux in pan-Arctic and Boreal Regions, 1989-2017
Bibliographic record
Abstract
This record is for the dataset “ Synthesis of Winter In Situ Soil CO2 Flux in pan-Arctic and Boreal Regions, 1989-2017” at https://doi.org/10.3334/ORNLDAAC/1692 This dataset provides a synthesis of winter ( September-April) in situ soil CO2 flux measurement data from locations across pan-Arctic and Boreal permafrost regions. The in situ data were compiled from 66 published and 21 unpublished studies conducted from 1989-2017. The data sources (publication references) are provided. Sampling sites spanned pan-Arctic Boreal and tundra regions (>53 Deg N) in continuous, discontinuous, and isolated/sporadic permafrost zones. The CO2 flux measurements were aggregated at the monthly level, or seasonally when monthly data were not available, and are reported as the daily average (g C m-2 day-1) over the interval. Soil moisture and temperature data plus environmental and ecological model driver data (e.g., vegetation type and productivity, soil substrate availability) are also included based on gridded satellite remote sensing and reanalysis sources. This dataset can be downloaded at https://doi.org/10.3334/ORNLDAAC/1692
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| 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) | 0.012 | 0.009 |
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".