Department of Defense (DoD) Marine Unexploded Ordnance (UXO) Site Database
Bibliographic record
Abstract
The majority of the DoD’s UXO detection and discrimination technology development efforts in the past have focused on terrestrial (land-based) areas that were used for testing and training. DoD munitions testing and training operations, as well as past disposal operations, also have been conducted in marine, estuarine, and other underwater environments. Potential human contact with underwater ordnance at or near these sites can include direct contact when swimming, diving, wading, or through indirect contact like anchoring, fishing, or dredging. Site-specific factors such as water depth, turbidity, temperature, tidal actions, currents, storms, and bottom conditions present unique challenges that can significantly hinder the use of conventional UXO technologies at underwater sites. The database includes information on site locations and ranges, environmental conditions, munitions reported or suspected, and other site attribute information. The majority of the sites are formerly used ranges (Formerly Used Defense Sites [FUDS]), but the database also includes Base Realignment and Closure (BRAC) Sites, and active ranges. We focused on compiling data for sites within the United States or under the control of the DoD in some capacity. During our review of sites, we also compiled listings of international sites of concern. These include a loosely compiled set of sites from the United Kingdom, Canada, Australia, Japan, Russia, Estonia, and Serbia and Montenegro.To use the database, Microsoft Access must be installed
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.048 |
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".