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Record W4297948183 · doi:10.5957/icetech-2008-121

State of Art of Arctic EER

2008· article· en· W4297948183 on OpenAlexaboutno aff
Frank G. Bercha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)ArcticComputer scienceSystems engineeringThe arcticResearch programRisk analysis (engineering)EngineeringBusiness

Abstract

fetched live from OpenAlex

This paper describes developments in technologies, engineering and analysis, and regulatory provisions relating to arctic Escape Evacuation and Rescue (EER). The developing national and international regulatory performance based regime has necessitated the development of tools for the evaluation and setting of performance based goals such as availability and reliability requirements, mirrored in current draft Transport Canada and ISO standards. To facilitate the reliability assessment and consequent setting of reliability targets in the Canadian standards, a multifaceted research and development program was initiated in parallel with its regulatory developments. Full scale manned and model tests, engineering and computer simulation, and world wide consultations and studies on human performance in life threatening conditions, comprise this R&D program. Use of conventional EER systems and technologies has limited applicability in ice populated waters, requiring the development of systems and procedures suited to the environmental, operational, and logistical requirements of arctic offshore regions. The paper summarizes available and emerging regulatory, modeling and research, and technological developments in arctic EER and gives recommendations on a number of promising directions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.167

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 head0.008
GPT teacher head0.167
Teacher spread0.160 · 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 designBench or experimental
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

Citations1
Published2008
Admission routes1
Has abstractyes

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