Improved Target-Value Design Approach through the Integration of Environmental Performance and Reliability Theory
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.
Bibliographic record
Abstract
Stakeholders in the construction industry continually strive to improve processes at all levels in order to achieve better performance while remaining competitive and meeting client demands. The recent and rapid level of industrialization in the construction industry necessitates stronger integration into the practice of design, planning, and management. Moreover, it is essential to understand the impact of management decisions on the performance of the systems in a building—such as architectural, structural, and mechanical—in order to achieve a high level of compatibility among the various systems in a building throughout the lifecycle of the project. However, such integration and understanding is not supported by the current practice of design in the construction industry. Thus, it is important to develop the concept of target-value design (TVD), an adaptation of Target Costing for the construction industry, in the following aspects: (1) extend the concept of values from a cost-centric system to a multiple-value system, such as incorporating cost, time, and energy consumption into the evaluation equation; (2) incorporate the performance of systems in the building, accounting for the interdependencies amongst the components of the systems, and the effect of the values on the performance; and (3) provide a method for design assessment that increases the likelihood of meeting client values, achieving a high level of performance for the building systems. Thus, this paper proposes a framework that consolidates these three aspects to provide a decision-support tool that helps decision makers in the construction industry to ensure that the end-product meets stakeholder requirements (e.g., cost), while at the same time the building systems reach more efficient performance as one holistic system.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it