Spatially Constrained Scheduling with Multidirectional Singularity Functions
Why this work is in the frame
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Bibliographic record
Abstract
Traditional scheduling techniques do not consider explicitly the spatial constraints and coordination requirements of activities or are limited to one progress dimension. Yet in practice, each activity strongly depends on the available workspace within a physical location, which should be optimized by a careful spatial coordination. Therefore, it is necessary to broaden current scheduling toward the capability of expressing space, including directional movements therein. Singularity functions previously were applied to model work quantities and durations in linear schedules. This research develops novel singularity functions that incorporate two dimensions of space plus time into the activity model. Options for different directions can be created easily by transformations of the equations. An algorithm was developed that considers spatial constraints and movements at the activity level and generates valid solutions. A step-by- step solved example is illustrated by an axonometric projection of the resulting schedule, which provides significant time gains compared to traditional approaches.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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