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Record W2976198202 · doi:10.1051/e3sconf/201911600088

Environmental and social effects of the change of heat sources on the example of a selected quarter of tenement houses in Wroclaw

2019· article· en· W2976198202 on OpenAlexaboutno aff
Małgorzata Szulgowska–Zgrzywa, Magdalena Baborska-Narożny, Krzysztof Piechurski, Ewelina Stefanowicz, Agnieszka Chmielewska, Natalia Fidorόw-Kaprawy, Marta Laska

Bibliographic record

VenueE3S Web of Conferences · 2019
Typearticle
Languageen
FieldEngineering
TopicBuilding energy efficiency and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Consumption (sociology)PollutantEnergy consumptionNatural resource economicsEnvironmental scienceEconomyBusinessEnvironmental engineeringEnvironmental protectionEngineeringEconomicsGeographyArchaeologySociology

Abstract

fetched live from OpenAlex

The energy consumption for space heating and domestic hot water preparation are significant burdens of a polish household budget, especially in old tenement houses. Simultaneously, lowering the emission of pollutants is under the great importance and one of main goals to achieve in big cities. This policy results in the need of elimination of systems based on solid fuels. The article analyses the environmental and social consequences of the exchange of heat sources in such buildings in one of the quarters in Wroclaw. It presents how this change will affect the levels of low emission and costs of energy supply to tenement buildings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.180
Teacher spread0.171 · 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 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
Published2019
Admission routes1
Has abstractyes

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