Longyearbyen CO<sub>2</sub> lab project—from a vision of a CO<sub>2</sub>-neutral Svalbard to a geoscience data eldorado
Bibliographic record
Abstract
The Longyearbyen CO 2 lab project was initiated in 2006 by the University Centre in Svalbard (UNIS) to establish whether subsurface storage of locally produced CO 2 is feasible. Over a decade of drilling operations and geoscientific research concluded that the subsurface was suitable for storing the CO 2 generated from the local power plant. The geological ingredients for successful CO 2 storage are in place, comprising a ca. 300 m thick, sandstone-dominated reservoir rock capped by an impermeable mudstone-dominated succession. No CO 2 was ever injected for storage in Svalbard for economic and political reasons. However, the project generated a wealth of new data, some of which proved critical for studies related to CO 2 storage elsewhere. The data were also key to the characterization of fluid flow and geothermal potential in Svalbard, deciphering past climatic changes, unravelling past tectonic events, some of relevance for understanding the plate tectonic evolution of the Arctic, as well as updating the global geological timescale. In this contribution, we briefly outline the history and main achievements of the Longyearbyen CO 2 lab project, before describing, categorizing and openly sharing the publicly available data from the project, including peer-reviewed publications (123 so far) and theses (18 PhD and 34 MSc).
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".