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
Critical path method delay analysis techniques are widely applied in the construction industry, with the windows method being regarded as technologically advantageous. The approach looks at different schedule snapshots (windows) throughout the project and analyzes the contractor versus owner responsibility for delaying the critical paths. Accordingly, decisions regarding time and/or cost compensation could be made. While the technique is beneficial, it is computationally intensive and produces different results with different window sizes. Commercial software provide little support in this regard and the analysis is usually done manually. In this paper, a modified windows approach is introduced with computerized daily analysis of delays so that accurate and repeatable results are produced. The new approach is coupled with a new representation of progress information and is readily usable by professionals and researchers to evaluate project delays. Details of the daily analysis are introduced along with two case studies that demonstrate its advantages over the traditional windows approach. A downloadable version is made available for experimental use by researchers and professionals.
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 | 0.002 | 0.001 |
| 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) | 0.000 | 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