Bibliographic record
Abstract
Worldwide vast experience exists, dating back to 1915, for liquid and gaseous hydrocarbons storage deep underground in geological strata/traps. Storage options include salt caverns, porous rock (depleted hydrocarbon fields or saline aquifers), abandoned mines and mined (unlined or lined) rock caverns, which offer opportunities for compressed air energy storage (CAES). Underground storage presents a number of benefits, notably very large volumes of gas (including air) stored at high pressures (up to 200 MPa), a small footprint with low environmental impact and considerable protection against external influences. CAES plants using solution-mined salt caverns have operated commercially since 1978 (Huntorf, Germany) and 1991 (McIntosh, Alabama, USA). Despite many studies, proposals and tests in most underground storage types since the 1970s, no further commercial plant was commissioned until 2019 with an ACAES plant at Goderich (Ontario, Canada), utilising a former brine cavern. The development and increasing integration of inherently intermittent renewable energy sources into the electricity grid means that CAES is once again being considered to provide rapid response, bulk energy storage, load-levelling and grid-scale support. Various CAES test types have commenced in salt caverns, tunnels and areas of abandoned mines. Options for geological storage, CAES development to date and some key considerations are briefly reviewed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".