GeoRoute: an interactive graphics system for routeing and scheduling over street networks
Bibliographic record
Abstract
The system components, computer configuration, and databases of a multi-purpose graphical tool for applications requiring a network representation of streets in urban and rural areas are described. The underlying data structure is adapted to routeing and scheduling problems for various types of delivery and public works vehicles requiring information about street-to-street connectivity, one-way streets, street types, and illegal turns at intersections. GeoRoute includes the functions required to keep the geographical database up-to-date, locate items on the street network, automatically and/or interactively generate optimized vehicle routes, and produce color maps using standard plotting devices. The street database is stored using an original street segment coding scheme; links are exploded when required for maps or displays. This structure allows large urban networks to be treated globally on standard personal computers running MS-DOS. GeoRoute is being used in a variety of situations, including trip planning for transit customers (based on both planned and real-time schedules), route optimization for armored cars, milk pick-up in rural areas, and public works planning.>
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.083 | 0.018 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".