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Record W2248210160 · doi:10.1504/ijhfe.2015.073009

Operational functionality test of offshore helicopter seat harness in wet and dry conditions

2015· article· en· W2248210160 on OpenAlexaff
Michael J. Taber, Dylan Sanchez, David Haas McMillan

Bibliographic record

VenueInternational Journal of Human Factors and Ergonomics · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsMarine engineeringSea trialSubmarine pipelineUnderwaterMechanism (biology)AeronauticsComputer scienceTest (biology)SimulationAutomotive engineeringEnvironmental scienceEngineeringGeologyGeotechnical engineeringOceanographyPhysics

Abstract

fetched live from OpenAlex

Testing of offshore helicopter seat harnesses (S76, S92, and AW 139) was completed in realistic conditions to identify possible differences between underwater egress training harnesses and those used in actual helicopters. A weighted manikin (210 lb) was used in 24 dry trials, and five qualified instructors completed 34 underwater egress trials. Of the 58 trials, there were no (0%) release mechanism malfunctions. There were five trials (9%) in which the harness release mechanism did not fully disengage on the first attempt; however all five cases (100%) resulted when the harnesses were not fully tightened correctly or when the legs of the manikin created excessive friction against the release mechanism. Results clearly showed that even in the most extreme situation (90° unbalanced load of 210 lb), the harnesses were capable of opening with only minimal force. It is recommended, however, that individuals fully tighten their seat harness prior to critical phases of flight.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.294
Teacher spread0.245 · 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 designObservational
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

Citations2
Published2015
Admission routes1
Has abstractyes

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