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Record W2070160092 · doi:10.1115/jrc2014-3750

Validation of the Accessible Lavatory Recommendations for the Next Generation of Accessible Passenger Rail Cars

2014· article· en· W2070160092 on OpenAlexaboutno aff
K M Hunter-Zaworski, Robin E. Kiff, Melissa Shurland

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsTransport engineeringComputer scienceWork (physics)Scale (ratio)Engineering

Abstract

fetched live from OpenAlex

The accessible lavatory specifications are part of the recommendations for specifications of the Next Generation of Passenger Rail Vehicles. These are being validated using virtual tools to model wheeled mobility aids with occupants using “concept” lavatories to determine optimal spatial configurations for accessible lavatories on board passenger rail vehicles. The overall project objectives included the development of accessibility specifications for the single and bi-level cars that can be used by the rail manufacturing industry to produce vehicles for high speed (HSR) and intercity passenger rail. The specific objective includes developing “virtual” models of accessible lavatories that incorporate the recommended accessibility specifications reported in paper No. JRC 2013-2554 in the proceedings of the 2013 Joint Rail Conference. The “virtual” models will permit both calibration and validation of the recommendations that were submitted to the PRII A Accessibility Working Group (the Working Group). The Working Group requested that prior to acceptance of the recommendations that they be validated and calibrated. The use of “virtual” validation tools and models permits the development, validation and calibration of different lavatory concepts and configurations prior to any future full scale testing. The construction and testing of full scale models is expensive, and some of the costs can be defrayed through the use of virtual modeling. This project extends the work undertaken in the development of the draft specifications for the accessibility of next generation of passenger rail cars. The draft specifications increase the size of both the wheeled mobility devices and occupants as a reflection of the changes in population demographics, this has prompted the need to develop new accessible lavatories that are more inclusive for the user, and still meet the design constraints of the vehicle builders. The project uses the new recommended design parameters for wheeled mobility devices and the draft guidelines for new accessibility features. Current accessible lavatories that are used on VIA Rail cars in Canada, and the TALGO and the Acela in the US serve as base models for the 2-D and 3-D renderings. These designs are optimized, validated, and calibrated with mannequins that represent the 5th and 95th percentile populations on large wheeled mobility devices including; sport manual wheelchairs, power wheelchairs and 4 wheel scooters that meet the 30 inch wide by 54 inch long footprint. It is known that some accessible lavatories that on are on existing rolling stock do not meet the needs of all customers. This project will provide quantitative measures to evaluate current designs and recommend future designs that are more inclusive.

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)0.021
metaresearch head score (Gemma)0.045
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: none
Teacher disagreement score0.037
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0050.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.005

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 head0.074
GPT teacher head0.274
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

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

Citations0
Published2014
Admission routes1
Has abstractyes

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