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Record W2889214146 · doi:10.1002/cepa.864

An innovative application of autoclaved aerated concrete technology

2018· article· en· W2889214146 on OpenAlexaff
Frank W. Riepe

Bibliographic record

Venuece/papers · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsAutoclaved aerated concreteCommercializationEngineeringBlock (permutation group theory)Thermal resistanceArchitectural engineeringCivil engineeringBusinessThermalMarketing

Abstract

fetched live from OpenAlex

Abstract Autoclaved aerated concrete (AAC) has failed to gain a foothold in the North American construction market despite its popularity in Europe. In North America the most common wall construction technology with a stucco finish, except in certain niche markets, is the exterior insulation finish system (EIFS). Because of the limitations of EIFS, a wall assembly technology has been developed that marries frame construction of all types with 75 mm thick AAC blocks and medium‐density sprayfoam polyurethane insulation. This composite technology allows more rapid assembly and higher performance than conventional AAC block construction. The completed stucco‐finished wall has much higher thermal resistance, load and shear strength, water and vapor resistance, and acoustical performance than single‐wythe AAC block construction. In North America, where AAC is used very little, this technology will allow much broader acceptance as even more benefits will be realized over prevailing technologies. This technology, known as System5zero, has two patents in the United States and is approaching commercialization. This paper and presentation will discuss development, testing, benefits, and applications of System5zero.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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