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Record W4412277443

Testing the Water: Applying BIMCO AUTOSHIPMAN to Remotely Controlled Ships, Cyber incidents and Events of Force Majeure

2021· article· en· W4412277443 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

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2021
Typearticle
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsForce majeureAeronauticsComputer securityEngineeringComputer sciencePolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

The full spectrum of the impact that contemporary technology pertains to remote control and automation on the management of ships that are equipped with such technology is unknown for the moment. However, the Baltic and International Maritime Council (BIMCO), the world’s largest membership organisation for shipowners, is developing a standard contract, AUTOSHIPMAN, which establishes the ground rules for allocation of tasks that concern the management of remotely controlled and autonomous ships. This standard contract contains both a cyber security clause and a force majeure clause. Cyber security being a modern concept, its implementation may be evaluated in the light of force majeure, so as to test whether they interplay. This research applies a ‘three-pillar test’ to examine whether it is possible for cyber incidents to fall into the scope of force majeure and aims to provide a well-rounded interpretation of the relevant provisions of this new standard contract before its full implementation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.002

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 head0.039
GPT teacher head0.240
Teacher spread0.200 · 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