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Teardown Index

2020· book-chapter· en· W3009094127 on OpenAlex
Joseph Dahmen, Jens von Bergmann, Misha Das

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

VenuePractice, progress, and proficiency in sustainability · 2020
Typebook-chapter
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOffset (computer science)Index (typography)Payback periodEfficient energy useArchitectural engineeringConstruct (python library)Environmental economicsEmbodied cognitionEngineeringBusinessComputer scienceEconomicsElectrical engineeringMicroeconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

Replacing older homes with new ones constructed to higher efficiency standards is one way to raise the operating efficiency of building stocks. However, new buildings require large amounts of embodied energy to construct, and it can take years before more efficient operations offset carbon emissions associated with new construction. This chapter looks at the carbon dioxide emission payback period of newly constructed, efficient single-family homes in Vancouver, British Columbia, where the authors find that it takes over 150 years for the operation to equal the embodied carbon associated with the of a typical high-efficiency new home. The findings suggest that current policies aimed at reducing emissions by replacing older homes with new high-efficiency buildings should be reconsidered.

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)0.001
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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