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 an automated system that integrates Global Positioning System (GPS) and Geographical Information System (GIS) in a web-based platform named Truck+. It is utilized for estimating, monitoring and forecasting productivity of hauling trucks in earthmoving operations. The developed system consists of GPS for automated site data acquisition, GIS web-based system used as graphical user interface, relational database and Discrete Event Simulation (DES) for stochastic forecasting. The paper also highlights the benefit of utilizing the actual captured data supported by DES for stochastically forecasting productivity of earthmoving operation. DES was applied to forecast productivity in a stochastic approach that makes use of the project’s captured data during the operations involved rather than data from past projects. This makes it more capable of capturing relevant factors that impact project conditions. Truck+ consists primarily of two modules: tracking/monitoring module and forecasting module. The developed system has been implemented in prototype software using object-oriented programming, ArcGIS APIs (Application Programming Interface) and deploys Microsoft Silverlight for creating and delivering rich internet web application and media. Truck+ is capable of generating graphical and tabular reports with various degrees of detail to suit the requirements of project teams. The developed system is applied to a construction project in Montreal area to demonstrate its use.
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 | 0.001 | 0.000 |
| 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