MétaCan
Menu
Back to cohort
Record W1996557610 · doi:10.1155/2013/216293

Moisture Transport for Reaction Enhancement in Fabrics

2013· article· en· W1996557610 on OpenAlex
Phillip Gibson, Heidi Schreuder‐Gibson, Pearl W. Yip, Brendan Denker, Hamid Benaddi, Sa Wang, Lev Bromberg, T. Alan Hatton

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Textiles · 2013
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsStedfast (Canada)
Fundersnot available
KeywordsMoistureWettingAdsorptionPerspirationMaterials scienceWater transportPermeationPolymerChemical engineeringComposite materialMembraneChemistryEnvironmental scienceEnvironmental engineeringOrganic chemistryWater flow

Abstract

fetched live from OpenAlex

The role of water in protective fabrics is critical to comfort and material performance. Excessive perspiration in clothing causes discomfort, and bound water can adversely affect the ability of carbon to adsorb chemicals. Yet the presence of water can also improve the moisture vapor transport of protective polymer films, and is essential for the hydrolytic destruction of nerve agents. Reported here are the findings of wicking and drying experiments conducted on various hydrophilic and hydrophobic cover fabrics that demonstrate the influence of wetting on permeation through fabrics. The influence of water content on reactive polymers capable of degrading nerve agent simulant is also discussed, and the importance of a novel “delivery system” for water to the reactive components through the use of a wicking fabric is introduced.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.345
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.280
Teacher spread0.257 · 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