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Record W4297796029 · doi:10.15485/1618871

Department of Defense (DoD) Marine Unexploded Ordnance (UXO) Site Database

2009· dataset· en· W4297796029 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2009
Typedataset
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsUnexploded ordnanceEngineeringDatabaseGeographyComputer scienceArchaeology

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.213
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it