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Application of air-source heat pump (ASHP) technology for residential buildings in Canada

2019· article· en· W2982163920 on OpenAlex
Artur Udovichenko, Lexuan Zhong

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHeat pumpEnvironmental scienceResidence time (fluid dynamics)Air source heat pumpsHeating systemResidenceMeteorologyHeat exchangerMechanical engineeringEngineeringGeography

Abstract

fetched live from OpenAlex

Abstract The air-source heat pump (ASHP) is a relatively new, highly efficient technology which has been proven to be a feasible alternative in mild temperature climates. However, an ASHP’s application tends to be limited by outdoor temperature in cold climate zones. This study was intended to explore the feasibility of ASHPs in conjunction with traditional furnaces to serve as an innovative energy efficient method for heating homes in Canada. The goal was to quantify the cost and emissions savings of an ASHP hybrid heating system as compared with a furnace-only system for a residence in three Canadian cities. A prototypical residential building with a hybrid heating system was generated for heating load calculations. The theoretical analysis included the determination of the outdoor-temperature-dependent heat loss rate from the residence and heat supply rate of ASHPs. The building model has proved to be useful for further analyses, while the feasibility of the hybrid system has been determined to be highly region dependent.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.980

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 head0.004
GPT teacher head0.170
Teacher spread0.167 · 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