A product exchange format for the defense mapping agency's vector products
Bibliographic record
Abstract
The Defense Mapping Agency (DMA) has recently, developed the Vector Product- Format (VPF). This standard for generating digital geographic information in vector format will be used to provide digital products to users. The standard has been designed to support; a wide range of products; and allows direct access to the data from its’ storage media without prior conversion to a working format. The standard was developed in cooperation with the military mapping agencies in Australia Canada, and the United Kingdom. Released simultaneously with the standard, the Digital Chart, of the World (DCW) is the first in a family of DMA vector products to use the VPF. It carries planimetric and topographic information equivalent to, the resolution1 of a 1.1 million scale chart and provides global coverage. The DCW is listed as a public release product to be sold by the co-developer nations. In the United States the sales agent is the United States Geological Survey (USGS). DMA is also prototyping other vector formatted products with appropriate data resolution and content, which will support its customers with manageable sources of geographic information.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.363 | 0.364 |
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".