Apportioning Concurrent Delays and Accelerations Using Daily Windows
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
Project as-built duration is the resultant of all day-to-day events and actions, including slowdowns, work stops, and accelerations, made by all project parties. In current practice, however, a systematic procedure for recording and analyzing daily actions is lacking, thus making the quantification and analysis of time-related and cost-related claims a complex task that is highly controversial. In this paper, a practical model is presented, with an analytical framework, for analyzing project as-built schedules, considering slowdowns, work stops, and accelerations. The model differentiates between owner-directed and contractor-voluntary accelerations and deals with acceleration as a negative delay attributable to the party that creates it. To provide accurate and repeatable results, the model uses a daily windows analysis technique for apportioning concurrent delays and accelerations. Details of the proposed model are provided along with an example application. The model is readily usable by professionals and researchers to dynamically analyze the impact of all events along project duration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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