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Record W4235122946 · doi:10.2172/15014835

Analysis of System Strategies Targeting Near-Term Building America Energy-Performance Goals for New Single-Family Homes: FY 2004 Fourth-Quarter Building America Milestone Report

2004· report· en· W4235122946 on OpenAlexaboutno aff
Rick Anderson, C. Christensen, G. Barker, Scott Horowitz, Aisling E. Courtney, T. Givler, K. Tupper

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
FundersNational Renewable Energy LaboratoryU.S. Department of Energy
KeywordsMilestoneQuarter (Canadian coin)Term (time)Architectural engineeringEngineeringOperations researchComputer scienceGeography

Abstract

fetched live from OpenAlex

The Building America residential systems research project uses an analysis-based system research approach to (1) Identify research priorities, (2) Identify technology gaps and opportunities, (3) Establish a consistent basis to track research progress, (4) Increase the cost effectiveness of research investments by identifying system solutions that are most likely to succeed as the initial targets for residential system research projects. This report describes the technical approach used by Building America to determine the most cost effective pathways to achieve whole-house energy savings goals. The report provides an overview of design/technology strategies leading to net zero energy buildings as the basis for analysis of future residential system performance. The analysis approach is demonstrated by providing an initial comparison of the least-cost options required to achieve 40% energy savings in five climate zones. The preliminary results from this study will be validated against field studies and updated on an annual basis to reflect best available residential system cost/performance data from ongoing Building America research activities.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.772
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations7
Published2004
Admission routes1
Has abstractyes

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