Hybrid Simulation Environment for Construction Projects: Identification of System Design Criteria
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
Large construction projects are complex, dynamic, and unpredictable. They are subject to external and uncontrollable events that affect their schedule and financial outcomes. Project managers take decisions along the lifecycle of the projects to align with projects objectives. These decisions are data dependent where data change over time. Simulation-based modeling and experimentation of such dynamic environment are a challenge. Modeling of large projects or multiprojects is difficult and impractical for standalone computers. This paper presents the criteria required in a simulation environment suitable for modeling large and complex systems such as construction projects to support their lifecycle management. Also presented is a platform that encompasses the identified criteria. The objective of the platform is to facilitate and simplify the simulation and modeling process and enable the inclusion of complexity in simulation models.
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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 | 0.000 | 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