Location-Aware Scheduling and Control of Linear Projects: Introducing Space-Time Float Prisms
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
Space and time planning of construction activities is a key factor affecting safety and field performance in construction sites. When scheduling and controlling linear projects, identification of potential congestion and/or idling can assist in the timely execution of a project. With the advent of location-aware technologies, it becomes possible to track availability of resources in (quasi-)real time during project execution. This provides better oversight over the movement of materials, equipment, and workforce in the jobsite. Space and time floats are currently defined and used separately in the scheduling literature. In this paper, the concept of space-time floats is proposed as a new type of float to simultaneously consider space and time constraints. Space-time floats are envelopes for all possible movement patterns that an activity or its associated resources can take considering the time and space constraints of that activity. Simultaneous consideration of space and time floats makes it possible to trade-off one for the other, which is the significance of this new float. Introduction of the space-time floats into the schedules offers new possibilities to forecast the availability of resources at a specific time and location. Use of the space-time float for each activity also enables the scheduling and control methods to forecast potential zones and times of congestion between activities and detect activity idle times as well as actual and/or potential delays. Eliminating congestions and potential risks for delays have been shown to offer considerable advantages for linear projects. Generation of space-time float for each activity in the project also helps the project team to be informed about the space and time available to them at each time and location, respectively.
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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 | 0.003 | 0.001 |
| 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 | 0.000 |
| 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