Framework for target cost modelling in construction projects
Why this work is in the frame
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Bibliographic record
Abstract
Target costing (TC) is an effective construction management technique that has been proven to enhance project performance through the evaluation of construction component alternatives that satisfy a desired cost. However, current research focusing on the adoption of TC in the construction industry still follows a manual, time-consuming process. Improvement measures are heuristic and rely on the intuition of designers. This paper proposes a systematic framework, called target cost modeling (TCMd), for the application of TC in the construction industry to automatically generate a detailed project estimate based on a set of client requirements and a desired cost. It uses a three-level database to collect project data and generate a set of available alternatives. Value and compatibility studies govern the process of selecting among alternatives, and mathematical costing models calculate the cost accordingly. Finally, alternative value analysis improves the project value through the use of an optimization method, simulated annealing. TCMd is expected to efficiently improve project performance and enhance the design process while meeting a desired overall cost.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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