Production prediction of conventional and global positioning system–based earthmoving systems using simulation and multiple regression analysis
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
Accurate estimation of construction production, which is composed of productivity and unit costs, allows construction planners and managers to have excellent control over current processes and to correctly predict the production of similar projects in the future. Due to the need for accurate production estimation, selection of the appropriate construction technology is a critical factor in the success of a project. This paper presents a methodology for developing a model capable of predicting productivity and unit costs using several procedures, such as actual data collection, input data generation using construction simulation, and multiple regression analysis. An earthmoving operation was analyzed to estimate the proposed methodology’s prediction of construction production. A global positioning system (GPS)–based earthmoving system was selected as the new construction technology to be compared with the conventional system, to evaluate the decision-making process at a jobsite. The proposed methodology is expected to provide users with a basis for selecting appropriate technology. The case study presented in this paper demonstrates how to utilize the proposed methodology and analyze its predicted results.
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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