Deterministic models for assessing productivity and cost of bored piles
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
The assessment process of productivity and cost of bored pile construction is dictated by unseen subsurface obstacles, lack of contractor experience and site planning. These problems complicate the estimator's role in evaluating pile equipment productivity and cost. Current research discusses the assessment of piling process productivity and cost using the deterministic technique. Data are collected through questionnaires, site interviews and telephone calls to experts in various construction companies. Many variables have been considered in the piling construction process, such as pile size, depth, pouring method, soil type and construction method. Five deterministic models have been designated to assess productivity, cycle time and cost. The developed models are validated whereas 79% of the outputs have been predicted with more than 75% accuracy. Consequently, three sets of charts have been developed to provide the decision‐maker with a solid planning, scheduling and control tool for piling projects. If a pile has 60′ depth with φ‐18 (18″ diameter pile) in clay soil using a 5′ auger height, the cycle time is estimated as 56 and 65.5 minutes; however, productivity is 6 and 5 holes/day for dry and wet methods, respectively.
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