MétaCan
Menu
Back to cohort
Record W4200570595 · doi:10.5750/ijme.v152ia3.832

NAVAL SHIP STABILITY GUIDELINES: DEVELOPING A SHARED VISION FOR NAVAL STABILITY ASSESSMENT

2021· article· en· W4200570595 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe International Journal of Maritime Engineering · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsCrewSoftware deploymentAeronauticsContext (archaeology)ProcurementOperations researchStability (learning theory)Computer scienceEngineeringLawComputer securityPolitical scienceBusinessHistoryArchaeology

Abstract

fetched live from OpenAlex

Surface combatants are required to operate in conditions of high military threat and be capable of deployment to any area of conflict or crisis at any time. This requirement calls for the vessel and crew to be capable of safely contending with the full range of environmental conditions that may be encountered while pursuing their primary objective. Achieving and maintaining this capability is strongly influenced by the application of naval stability standards, many of which have a common origin, based on experiences from the World War II and before. Although such standards have apparently served the navies admirably over many years, there are many reasons to question their limitations and applicability in the context of modern ship design and procurement. This paper presents the efforts to date of the Naval Stability Standards Working Group to investigate the relationship between existing intact stability standards and capsize risk with respect to frigate forms.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.364
Teacher spread0.295 · 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