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Energy Efficiency of Low Quality Built Heritage: Methodological Reflections on Achieving the NZEB through a Case Study in the City of L'Aquila

2018· article· en· W2792745270 on OpenAlexvenueno aff
Elisa Ieie

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectural engineeringContext (archaeology)Zero-energy buildingEnergy consumptionQuality (philosophy)Renewable energyEfficient energy useEnvironmental economicsCivil engineeringEngineeringGeography

Abstract

fetched live from OpenAlex

About the building heritage and, in particular, about the widespread heritage without historical or architectural quality, it currently opens a challenge in perpetual evolution. This is the integration of innovative technological solutions for building regeneration, which can help a qualitative improvement of the living spaces and the reduction of energy consumptions. Context factors, the intensity of precipitation, the different types of soil, and the amount of solar irradiation or wind speed are doubtless the main causes of the degradation of the existing buildings. On another way, through the control of climatic and biophysical parameters, the focus on the properties of materials and a careful design process, these variables can increase the use of renewable energy sources, becoming environmental resources to reduce energy consumption, to provide comfortable living spaces and aiming the realization of a Near Zero Energy Building. The paper proposes a reflection on the main methodological issues emerged in the hypothesis of intervention experimented on a case study in the city of L'Aquila. The building, located near the historical center of the city, is in direct relation with important pre-existences such as the Forte Spagnolo and the San Salvatore hospital. It is an example of possible regeneration of low quality building in which the additional use of new functional spaces can increase not only energy performances, but also an increase of architectural value of the building.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.204
GPT teacher head0.431
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2018
Admission routes1
Has abstractyes

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