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Record W6986635123

Properties of vacuum insulation panels: results from experimental investigations at NRC Canada

2004· article· en· W6986635123 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsPermeanceWater vaporThermal insulationRelative humidityHumidityThermalCore (optical fiber)Enhanced Data Rates for GSM Evolution
DOInot available

Abstract

fetched live from OpenAlex

Many samples of commercially available vacuum insulation panels were tested in the laboratory to determine their physical properties such as thermal resistance, water vapour permeance of the foils and sorption characteristics of the core material. The effect of various exposure conditions, which includes 32 ºC, relative humidity up to 90 % and 5 bar over-pressure, on the thermal resistance was determined. Also, the edge effects when panels were put side by side were evaluated. The performance of the sealing foils and seams in the manufactured products was checked in terms of water vapour permeance and air permeance. The tested products seem to with stand major environmental loads. High humidity, higher temperature and even higher pressure have not significantly changed their thermal resistances in two years. Air permeance across the foils is immeasurably low. Water vapour does permeate, albeit at a very low rate(1 to 3 ng m-2 s-1 Pa-1), across the foils and seams. However, precipitated silica as a core material has appreciable capacity to adsorb and store water molecules. Though the central portions of the panels show remarkable thermal resistances, the edge effect for the same reason is significant. The joining point of the four corners of four high performance panels is only as efficient as a high performance cellular plastic insulation.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.221
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 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
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
Published2004
Admission routes2
Has abstractyes

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