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
Construction projects are complex, from their design to the execution phase. Delivering a project on time is unpredictable due to the inherent uncertainty. Delays are normally considered to be an inseparable part of construction projects. Delays often lead to claims for costs incurred. Assessing construction claims caused by delays is complicated, as are the proceedings for achieving claim resolution. Loss of anticipated revenue, opportunity cost, increased overhead, cost escalation and liquidated damages are some of the main reasons for delay claims from key project stakeholders. A sound request for a delay claim must be supported by a reliable delay analysis technique. This paper discusses a new technique that is capable of evaluating concurrent delays. The technique is windows-based; therefore, it can trace all of the changes in the critical path(s). Apportionment of delay accountability may result in a false outcome if the effect of concurrent delays and changes in the critical path is overlooked. The procedures of this proposed technique are explained. The technique was tested against a hypothetical case and compared to existing delay analysis techniques with satisfactory results. The proposed technique allocates delays among the different project parties.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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