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Record W7100247032

Diminishing Energy Consumption in Heating and Cooling Passive Houses Using Geothermal Energy

2012· article· en· W7100247032 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsEnergy consumptionHeat exchangerConsumption (sociology)Energy (signal processing)Section (typography)Geothermal gradientGeothermal energy
DOInot available

Abstract

fetched live from OpenAlex

The paper is divided into five parts. In the first the importance of increasing the energy performance of buildings is set into evidence under the circumstances in which the buildings are responsible for a considerable input as considering both energy consumption and green house effects emissions. In view of meeting the objectives of energetic policies the emphasis will be set on the passive house standards and its advantages as significant energy consumption is concerned. In the second section the paper presents the system of exploiting the shallow thermal potential of earth, by using earth – air heat exchangers also known as Canadian wells. In the third section, the mathematic model is presented that is laying at the basis of Canadian wells systems analysis, in dynamic system with simulating soft. In the fourth part the results of Canadian wells system analysis are presented and in the fifth part the paper comes up with the conclusions referring to the influences of various parameters upon improving the performances of these systems. Rezumat Lucrarea este împărțită în cinci părți. În prima parte este evidențiată importanța creșterii performanței energetice a clădirilor, în condițiile în care clădirile sunt răspunzătoare de un aport

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.258
Teacher spread0.225 · 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 designSimulation or modeling
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
Published2012
Admission routes1
Has abstractyes

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