Polaris Project 2017: Vegetation biomass, carbon, and nitrogen, Yukon-Kuskokwim Delta, Alaska
Bibliographic record
Abstract
This project is integrating scientific research in the Arctic with education and outreach, with a strong central focus on engaging undergraduate students and visiting faculty from groups that have had little involvement in Arctic science to date. The central element of the project is a month-long research expedition to the Yukon River Delta in Alaska. The expedition provides a deep intellectual and cultural immersion in the context of an authentic research experience that is paramount for "hooking" students and keeping them moving along the pipeline to careers as Arctic scientists. The overarching scientific issue that drives the research is the vulnerability and fate of ancient carbon stored in Arctic permafrost (permanently frozen ground). Widespread permafrost thaw is expected to occur this century, but large uncertainties remain in estimating the timing, magnitude, and form of carbon that will be released when thawed. Project participants are working in collaborative research groups to make fundamental scientific discoveries related to the vulnerability of permafrost carbon in the Yukon River Delta and the potential implications of permafrost thaw in this region for the global climate system. This data set includes vegetation biomass, %C, and %N results from the 2017 expedition.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".