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Record W2136735913 · doi:10.4271/2002-01-0222

Thermal Comfort Analysis of an Automobile Driver with Heated and Ventilated Seat

2002· article· en· W2136735913 on OpenAlexafffund
Gholamreza Karimi, Edward C. Chan, J. R. Culham, I. Linjacki, Liam Brennan

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2002
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutomotive engineeringCar seatThermal comfortComputer scienceThermal analysisAeronauticsThermalEngineeringPhysics

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">A thermal/physical model of the dynamic interaction between an automobile passenger, the cabin environment, and a heated/ventilated seat is presented. The model considers the human body as being made of 21 distinct segments and three-layers. Simple mathematical models are presented to simulate heating and ventilation of cool air through the seat.</div> <div class="htmlview paragraph">The model has the ability to predict the transient response of a driver in a highly non-uniform thermal environment in terms of local and overall thermal comfort levels.</div>

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.214
Teacher spread0.205 · 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.

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

Citations28
Published2002
Admission routes2
Has abstractyes

Explore more

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