Bibliographic record
Abstract
Abstract An inventory of the surface area and volume of the world’s glaciers, outside Greenland and Antarctica, was part of the International Hydrological Decade (1965–74). It was considered essential to an understanding of the role played by glaciers in the hydrological cycle and was to be repeated every 50 years to detect change. To date, 46% of the estimated total glacier area has been inventoried and made available through the World Glacier Monitoring Service and the US National Snow and Ice Data Center. As the original inventory method was too time-consuming and inapplicable for some areas, a simplified method was developed in the early 1980s using satellite images. The Global Land Ice Measurements from Space (GLIMS) project now covers 34% of the estimated glacierized area outside Greenland and Antarctica. Both inventory efforts have made good progress and contributed substantially to our knowledge of glaciology and its related sciences, but global coverage is still incomplete. If both inventories are combined, 46% of the world’s glacierized area is still missing; 26% is covered by both methods, which allows the quality of the satellite-based and semi-automatic inventories to be assessed by comparison. About 95 000 glaciers remain to be inventoried, of which about half are in the Canadian Cordillera, South America and the Canadian Arctic Islands. As the cryosphere is changing rapidly, it is of the utmost importance to complete the global glacier inventory as soon as possible, and identify an appropriate repeat cycle.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".