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Record W4392548583 · doi:10.2478/remav-2024-0003

Analysis of Environmentally Certified Residential Developments in Poland

2024· article· en· W4392548583 on OpenAlexaboutno aff
Alina Kulczyk-Dynowska, Aleksandra Nowicka

Bibliographic record

VenueReal Estate Management and Valuation · 2024
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
FundersUniwersytet Przyrodniczy we Wrocławiu
KeywordsCertificationScope (computer science)Investment (military)BusinessQuarter (Canadian coin)Scale (ratio)Distribution (mathematics)Environmental economicsEnvironmental protectionEnvironmental resource managementEnvironmental planningEnvironmental scienceGeographyComputer scienceEconomicsCartographyPolitical science

Abstract

fetched live from OpenAlex

Abstract The scale of environmental pressure caused by the construction sector has prompted a search for new technical solutions to minimize the negative impact of this part of the national economy on the environment. The drive to evaluate the adopted solutions has led to the creation of building assessment systems - environmental certificates. The aim of the article is both to introduce the certification processes used in the Polish residential property market and to indicate the locations of residential investments that have obtained the certificates in question. The paper takes a closer look at environmental certification using multi-criteria building assessment systems, i.e. BREEAM, LEED and HQE. The time scope of the presented research covered the years 2016 to the first quarter of 2022. The research carried out allowed an upward trend to be observed in the number of environmental certificates awarded, indicating the use of green building principles for residential properties. It is certain that there has been a development of this type of investment in Poland in the recent years. An analysis of the spatial distribution of the surveyed investments shows that location clusters have formed - green (low-emission) residential investments are distributed in the largest cities in Poland, which are characterized by a strictly defined consumer profile.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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