Bibliographic record
Abstract
Abstract The World Glacier Inventory (WGI) was conceived half a century ago as an activity to be completed during the International Geophysical Year, 1957/58. It consisted until very recently of nearly 70 000 glacier records covering slightly less than one-quarter of the glacier ice outside the ice sheets. A complete WGI must be a compromise if it is to be available and usable soon. A more complete version, called WGI-XF, is available and usable now and contains records for just over 131 000 glaciers and nearly half of the global extent of ice. The additional glaciers come mainly from the assimilation of existing inventories but also from rescuing inventories that have been lost and from new inventories in Canada and the Subantarctic. In WGI-XF, the XF stands for ‘extended format’, flagging the fact that WGI-XF conforms to a set of explicit specifications which enhance usefulness by eliminating low-level inconsistencies. Two important features are nominal glaciers and glacier complexes. A nominal glacier, of which there are about 5000 in WGI-XF, is one about which little is known other than its existence and approximate location. A glacier complex is one or more contiguous glaciers. This term embodies the idea, which is not new, that inventories can be preliminary, based upon vector outlines which await subdivision by trained glaciologists. Many regional studies have found that measurements of changes in single glaciers require accurate work and painstaking quality control. WGI-XF is not assuredly reliable as a source for such detailed work, but there are several other subjects in which less detail would be a price worth paying for more complete coverage. Incomplete information about the dates of imagery and maps is a hindrance to analysis, and the recovery of dates from metadata should have high priority.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.103 | 0.062 |
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".