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Record W6947538638 · doi:10.4224/40003400

Resilient and smart air ventilation systems for northern housing CO₂-based demand controlled energy recovery ventilation system: Phase 2

2024· report· en· W6947538638 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2024
Typereport
Languageen
FieldMedicine
TopicFlavonoids in Medical Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsEnergy recovery ventilationVentilation (architecture)Energy recoveryWork (physics)Heat recovery ventilationIndoor air quality

Abstract

fetched live from OpenAlex

This report is part of the AQP project A1-020102 on Resilient and Smart Ventilation Systems for Northern Housing. The project is a continuation of the work done in previous projects on air ventilation systems for housing in the Arctic. The focus this time was on enhancing the identified resilient novel dual core energy recovery system and make it a smart air ventilation system for northern housing that will ensure proper ventilation, improved indoor air quality (IAQ), and with the final objective being to reduce health risks for Northern and remote communities. The aim of this project is to investigate the performance of a demand-controlled dual core regenerative energy recovery ventilator (ERV) to adjust ventilation to the specific indoor needs. This research combines the benefits of full demand-controlled air flows and energy recovery to ensure proper ventilation (meet ventilation requirement) of housing experiencing varying occupancy and overcrowding.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.036
GPT teacher head0.349
Teacher spread0.313 · 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.

Study designNot applicable
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
Published2024
Admission routes2
Has abstractyes

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