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Record W3081862985 · doi:10.1617/s11527-020-01547-z

Magnesium oxychloride boards: understanding a novel building material

2020· article· en· W3081862985 on OpenAlexfundno aff
Timothy A. Aiken, Mark Russell, Daniel McPolin, Leo Bagnall

Bibliographic record

VenueMaterials and Structures · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Oxide Properties and Applications
Canadian institutionsnot available
FundersInnovate UKQueen's UniversityQueen's University BelfastInvest Northern Ireland
KeywordsMagnesiumGypsumDurabilityMaterials scienceCementComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Abstract Magnesium oxide type building boards are a relatively new alternative to traditional sheeting materials such as plywood, gypsum plasterboard and fibre-cement board. They have many advantages; strength, lightweight, ease of use and excellent fire resistance, which has become increasingly important as demanded by industry and required by more stringent legislation. Recently cases of durability issues associated with magnesium oxychloride boards in Denmark have emerged, however the precise nature of the problem was not established. These issues have been related to magnesium oxychloride boards which were exposed to high levels of moisture. In this paper the mechanism of the failures observed in Denmark has been investigated. The difference in quality between various magnesium oxychloride boards available in the market was also studied. It was found that there are significant differences, both physically and chemically, between magnesium oxychloride boards supplied from different manufacturers. Crucially, the performance of each board when exposed to high levels of relative humidity was vastly different. Some of the boards investigated displayed behaviour similar to that observed in Denmark, whilst other boards exhibited substantial resistance to humid environments and had not deteriorated after 60 weeks of exposure.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.046
GPT teacher head0.241
Teacher spread0.195 · 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

Citations44
Published2020
Admission routes1
Has abstractyes

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