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Record W2050290137 · doi:10.3992/jgb.4.3.61

Buildings Alive! Establishing the Cost of Living Buildings Striving for Net Zero Performance

2009· article· en· W2050290137 on OpenAlexaboutno aff
Elizabeth J Heider, Clark Brockman

Bibliographic record

VenueJournal of Green Building · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectural engineeringZero-energy buildingZero (linguistics)Zero emissionNet (polyhedron)Green buildingEngineeringCivil engineeringEnvironmental scienceEfficient energy useMathematicsWaste managementElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Innovative ideas have helped bring us some of the most incredible technological advances the world has seen. These ideas have ranged from the practical—“classic” inventions like the telephone—to the out-of-this-world. Who would have believed 15 years ago that today, in 2009, we are literally on the cusp of space tourism. As incredible as the thinking was behind those innovations, there is another element that affects whether or not inventions catch on in a meaningful way. As remarkable as many inventions are, we know that it takes more than innovation to bring big ideas into reality—it takes a deep understanding of what things cost, and of the value that objects or ideas will deliver over time. We all have a telephone, but few of us will ever ride into space. And the reason behind this is simple: cost. Some mobile phone companies will give you a phone for “free” if you purchase an ongoing service plan and, by contrast, a ride on Virgin Galactic is likely to cost more than your home. Big, expensive, stretch goals benefit from challenges like the X Prize—the original competition that asked private entities to put someone into space and bring him or her home safely. This contest in particular, helped establish the baseline costs of private space flight. Without costs, we cannot plan. We all might say we would pay for the opportunity to go to space, but without a tangible cost of doing so, we cannot possibly be sure, or sincere. Only when a cost has been estimated, can we budget and begin to make solid plans. Unlike rocketing off into the ether, green building offers a bottom line return on investment. Green builders have already put together documented evidence of how quickly the upfront costs of building green can be recouped due to energy and resource savings—savings that have propelled the adoption of LEED standards for new construction by both public agencies and private real estate owners. But even a LEED Platinum building, as cutting edge as it is in today's market, still has a significant carbon footprint. Enter the concept of a “Living Building,” a facility that generates as much energy as it consumes and only uses as much water as falls on its site in a year. This has seemed to many to be an idea that is still quite far off. Assumed to be far too expensive to execute, Living Buildings have been considered “bleeding edge,” if not altogether impossible, mostly because of misperceptions around first cost. Without knowing what Living Buildings might truly cost and what return on investment they might provide, Living Buildings may have remained an after-dinner conversation topic rather than a discussion for the boardroom. The task of changing cultural and social paradigms like these falls to those who are willing to disprove what is perceived as impossible. In the three years since the Living Building Challenge was announced—the green building industry's “X Prize”—there has been phenomenal interest from clients and design firms attracted by the elegance and simplicity of the concept and an appreciation for the new milestone it defines on the path toward a restorative future. Often, the questions that arise after building owners begin to comprehend the magnitude of the Living Building Challenge are “What is the cost premium?” and “What might the payback be?” A study commissioned by the Cascadia Green Building Council, a chapter of both the U.S. and Canadian Green Building Councils, takes direct aim at those very questions, and the results are enlightening and encouraging.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.492

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 communication0.0000.001
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 head0.016
GPT teacher head0.264
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes1
Has abstractyes

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