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Record W4298441805 · doi:10.5957/icetech-2010-108

Arctic Offshore Escape, Evacuation, and Rescue Standards and Guidelines

2010· article· en· W4298441805 on OpenAlexaboutno aff
James P. Poplin, Frank G. Bercha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSubmarine pipelineArcticPetroleumReliability (semiconductor)Offshore oil and gasSearch and rescueOffshore drillingWork (physics)Environmental scienceAeronauticsMarine engineeringEnvironmental resource managementEngineeringComputer scienceOceanographyGeology

Abstract

fetched live from OpenAlex

Arctic Escape, Evacuation, and Rescue (EER) is receiving more attention with the current resurgence of interest in Arctic offshore hydrocarbon reserves, marine tourism and shortening marine transportation routes. Since 2000, Transport Canada supported the Arctic EER research project for which the second author’s company has been the lead contractor. The research conducted under this program resulted in the development of Canadian performance-based standards for offshore petroleum installations and a computer model capable of assessing the reliability and performance of EER processes. The ISO, under Working Group 8, developed a Final Draft International Standard addressing Arctic Offshore Structures which is expected to be published in late-2010. The Standard addresses design requirements and assessments for Arctic offshore structures used by the petroleum and natural gas industries worldwide to help ensure that appropriate reliability levels are achieved for manned and unmanned offshore structures, regardless of the type of structure. The EER provisions of the Standard are intended to promote the successful escape from the incident, subsequent evacuation from the installation (emergency or precautionary evacuation), and the ultimate rescue of installation personnel. The EER provisions are performance-based. The Standard specifies design requirements and also provides background to and guidance on the use of the document.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.395

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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 designOther design
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
Published2010
Admission routes1
Has abstractyes

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