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Record W2079232359 · doi:10.3130/aije.73.1435

CO2 EMISSIONS FROM THE CONSTRUCTION AND USE OF WELL-INSULATED AND AIRTIGHT HOUSES BASED ON MEASUREMENT SURVEY

2008· article· en· W2079232359 on OpenAlex

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.

Bibliographic record

VenueJournal of Environmental Engineering (Transactions of AIJ) · 2008
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, Agriculture Analysis
Canadian institutionsEmissions Reduction Alberta
Fundersnot available
KeywordsCeiling (cloud)ScheduleElectricityEnvironmental scienceEnergy consumptionConsumption (sociology)Waste managementPassive houseEnvironmental engineeringAgricultural economicsEngineeringArchitectural engineeringEfficient energy useComputer scienceEconomics

Abstract

fetched live from OpenAlex

CO2emissions from the construction and use of houses have been increasing. In order to promote the reduction of CO2 , it is necessary to know the exact amount of CO2 emissions from houses. First, the authors measured the exact weight of the construction materials and waste. Next, the authors researched the inhabitants' daily schedule and measured the energy consumption from using the house . The following results were obtained.1) The authors discovered the relationship between the energy consumption and the inhabitants' daily schedule.2) The amount of electricity consumed was 30.6GJ/year for the first year and 28.9GJ/year for the second year.3) The amount of CO2 emissions from both the construction and two years use of the house was 389.07kg-CO2/m2.4) The authors recalculated the amount of CO2 emissions into the amount of CO2 emissions per area of ceiling, floor and outer wall to discover the relationship between CO2 emissions from the construction and CO2emissions from use of the house.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.518

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 head0.013
GPT teacher head0.166
Teacher spread0.153 · 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