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Record W4410459122 · doi:10.59297/30z9xh19

An Affordable, Capable Maritime Emergency Response System

2025· article· en· W4410459122 on OpenAlexaff
J. Dalziel, Shelley P. Gallup, Ronald Pelot

Bibliographic record

VenueProceedings of the ... International ISCRAM Conference · 2025
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEmergency responseDisaster responseBusinessEmergency managementMedical emergencyAeronauticsMedicineEngineeringEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Responding to emergencies for coastal communities in remote regions often involves a maritime (Coast Guard) component. However, Coast Guard ships can be few in number, widely dispersed, difficult to crew, expensive to operate and build. A solution to this problem from a Naval perspective has been proposed by the US Naval Postgraduate School; a relatively small and inexpensive vessel, lightly crewed operating with a flotilla of uncrewed surface vessels. From a Coast Guard perspective, this could assist with response to coastal community, offshore infrastructure and maritime emergencies, while at the same time provide maritime domain awareness, enhance coastal sovereignty, protect critical underwater infrastructure (an increasingly important part of life in the Arctic and worldwide) and respond to maritime search and rescue and pollution incidents. The Need, the Problem, a Solution and its Technology are explored. Potential applications are described.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.014

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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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