Bibliographic record
Abstract
Up in the highest reaches of the Central Andes, along the Sierra Nevada in California, along the European Alps, in some of the most unlikely places, including countries like Turkey, Bulgaria, Kosovo, Romania, Montenegro, Armenia, Azerbaijan, Afghanistan, Iran, and China, and in some more likely ones such as Mongolia, Russia, Nepal, Norway, Sweden, Argentina, Chile, and Canada, lie entire swaths of frozen lands containing enormous quantities of invisible water in a solid state, hidden from sight until the surrounding ecosystems call on these lands to provide summer meltwater. As much as 25% of the surface of the Earth’s land experiences these frozen conditions, and more than 9 million people live in such environments. Even more live immediately below these lands, and yet most of us have never even heard of this frozen realm. The Incas and the Aztecs are known to have used this frozen terrain to store and conserve food. I am not talking about the more obviously glaciated regions with visible white cover on high mountaintops (which also act as water towers and basin regulators), but rather of that strip of land that lies somewhere below the lowest limit of the visible glaciers and somewhere above the timber line. No ice or snow may be immediately visible in this region, but, sure enough, the Earth is storing colossal amounts of ice, protected from the warm ambient temperature, for when the environment needs it most. We can think of this invisible frozen region as a buffer or hydrological ice zone that ecosystems call on for steady water all year round. It’s what glaciologists call the periglacial environment. The term itself is somewhat deceiving. Peri suggests “perimeter” or “surrounding,” so we might guess that the periglacial environment is the area surrounding the glacier, a sort of buffer zone around the visible ice where logically some sort of cryogenic activity (freezing activity) is occurring. Although such activity may indeed be occurring around the fringes of any given glacier, this is not the area known as the periglacial environment. Periglacial environments are much more complex than their name might suggest.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.025 |
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".