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Record W6948116829 · doi:10.4224/17210697

Thermal manikin calibration method

2010· report· en· W6948116829 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2010
Typereport
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsCalorimeter (particle physics)CalibrationThermalRepeatabilityThermal manikinStandardizationIsothermal process

Abstract

fetched live from OpenAlex

In 2007 the International Organization for Standardization (ISO) established ISO/TC 188/WG 14 Thermal Manikin Working Group to study the suitability of using thermal manikins for approval testing and to propose updated wording to include manikins in ISO 15027-3 Immersion Suit Test Method. To systematically conduct research to investigate human and manikin equivalence, it is necessary to first establish a common, traceable calibration for thermal manikins, so there is confidence that thermal manikins accurately report temperatures, heat loss and power, and that differences in results among thermal manikins and manikin-human correlation are understood, quantified and accounted. The goal of this project is to develop a thermal manikin calibration method. It addresses the accuracy and repeatability of thermal manikins to accurately report heat loss, power and temperature. Without such a traceable standard, manufacturers and researchers will dispute differences in results from various thermal manikins. For this purpose, National Research Council Canada, Institute for Ocean Technology (NRC-IOT) constructed a calorimeter laboratory to house a full body water calorimeter transferred from Defence R&D Canada (DRDC). The design specifications of the calorimeter laboratory and water calorimeter are presented in this report. A submersible thermal manikin calibration method is proposed. The results show that the laboratory and the calorimeter meet all design specifications, specifically 1. The calorimeter stirring system was able to establish an isothermal condition within 10 minutes. 2. The stirring system does not generate more than 100 W of power over a 2-hour period. 3. Dye tests provided a visual means to assess and confirmed the stirring system performance. 4. Under regular control mode, the environmental chamber was able to maintain a user specified setpoint temperature to within ±0.1°C. 5. Under tracking control mode, the environmental chamber was able to maintain the air temperature at a fixed offset with respect to the water temperature in the calorimeter, which is specified by the user. 6. Using a 500W known heat source, it was demonstrated that the calorimeter could measure power accurate to within 1%. Using the calorimeter, the NEMO thermal manikin calibration was validated. The results show that the power reported by NEMO thermal manikin agrees with the calorimeter measured power to within 1% in both constant temperature and constant heat flux modes.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.037
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0040.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0370.026

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 head0.309
Teacher spread0.262 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2010
Admission routes2
Has abstractyes

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