Assessment of construction operations productivity rate as computed by simulation models
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Bibliographic record
Abstract
Modeling and simulation tools are used to assist decision-makers to predict essential parameters such as completion duration and productivity rate of construction operations. Two approaches are used, process simulation and system simulation. The first compute parameters based on processes interaction while the second focuses on the complex relationship among project components and their impacts. This paper presents an assessment to simulated project completion duration and productivity rate under traditional Discrete Event Simulation (DES) and modified traditional simulation technique. The evaluation is based on a simulated real case study. The process elements of the case were simulated using (DES) while system elements were simulated using System Dynamics (SD). A significant difference in productivity rate and duration was noticed between the base DES model and the impacted model. The argument presented about the credibility of simulation model outcomes highlight the pitfalls of simulation models and the measures that should be endorsed.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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