An algorithm for mobile crane selection and location on construction sites
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
This paper presents a newly developed algorithm for selecting and locating mobile cranes on construction sites. The algorithm is incorporated into a computer system that integrates a selection module and three databases, dedicated respectively, for cranes, rigging equipment, and projects’ information. This paper focuses primarily on the selection module and its algorithm to support an efficient search for most suitable crane configurations and their associated lift settings. Data pertinent to crane lift configurations and settings are retrieved from the databases and processed to determine the near optimum selection of a crane configuration. The developed selection module features powerful graphics capabilities and a practical user-friendly interface, designed to facilitate the considerations of user imposed lift and site constraints. The selection algorithm has been implemented within the crane selection module using MS-Visual Basic programming language. A case example is presented in order to demonstrate the use of the developed selection module and to illustrate its essential features.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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