Investigation and ranking the causes of delay in EPC projects of nonindustrial buildings of 9, 10, 19, 20 and 21 phases of South Pars of Iran
Bibliographic record
Abstract
Delay is one of the most common causes of construction projects failure in Iran. The larger sizes of the projects, the more risks and costs of delays. In this paper, the causes of delays in EPC contracts of nonindustrial buildings were excavated from the related previous research and several interviews with experts of this subject, and adjusted by the brainstorming technique, Delphi and reconciling the nature of these projects. Then, a questionnaire was distributed among 52 experts working in the South Pars project, and the data were analyzed by descriptive and factor analysis methods. Descriptive analysis revealed that “Inflation and escalation of material prices and human resources salaries”, “Unrealistic contract duration and requirements imposed” and “Political situation” were the most significant delay factors. Meanwhile, factor analysis indicates that “Improper construction methods”, “Shortage of experienced and skilled labor” and “Long acceptance process (shop drawings, permits, tests and samples)” were the most important causes of delay.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".