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Record W183030786

Maritime Domain Awareness: A Western Hemisphere Imperative

2006· article· en· W183030786 on OpenAlexaboutno aff
James L. Minta

Bibliographic record

VenueDefense Technical Information Center (DTIC) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNorth Atlantic TreatyDomain (mathematical analysis)TerrorismMaritime securityPhase (matter)Multinational corporationPolitical scienceNational securityGeographyComputer securityComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

The National Strategy for Maritime Security states terrorists will most likely transport weapons of mass destruction into the United States via the maritime domain. Maritime domain awareness (MDA) is the understanding of the situation at sea to enable maritime security. Development of a comprehensive maritime domain awareness program is critical in preventing another terrorist attack on the United States. The focus of this project is to research a question posed by U.S. Northern Command concerning whether Canada and the United States should enter into a bi-national agreement for maritime domain awareness. My research lead me to the conclusion that to truly develop maritime domain awareness that will protect America a Western Hemisphere multinational treaty organization of willing states needs to be established to develop a common operational picture of the maritime domain. The project lays out a three-phase approach to establishing this organization beginning with establishing a bi-national agreement with Canada. Phase 2 is bringing Mexico into the organization which would include the transformation of Joint Interagency Task Force South into the Western Hemisphere Maritime Domain Awareness Center. The final phase develops the organization fully with willing nations in the Western Hemisphere contributing what they can to develop a complete regional common operational picture.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.013
GPT teacher head0.280
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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