Delay Analysis under Multiple Baseline Updates
Why this work is in the frame
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Bibliographic record
Abstract
Windows delay analysis has been recognized as one of the most credible techniques for analyzing construction delays. To overcome some of the drawbacks of windows delay analysis, this paper introduces improvements to a computerized schedule analysis model so that it will produce accurate and repeatable results. The model considers multiple baseline updates due to changes in the durations of the activities and the logical relationships among them, as well as the impact of resource overallocation. The model uses a daily window size in order to consider all fluctuations in the critical path(s) and uses a legible representation of progress information to accurately apportion delays and accelerations among project parties. A simple case study has been implemented to demonstrate the accuracy and usefulness of the proposed delay analysis model. This research is useful for both researchers and practitioners and allows detailed and repeatable analysis of the progress of a construction project in order to facilitate corrective actions and claim analysis.
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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 | 0.002 | 0.001 |
| 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