Analysis of the Variability of Parking Characteristics in A WeeklyDistribution in the Conditions of PPZ and DPI Functioning
Bibliographic record
Abstract
Positive changes in the number of cars parked in the city center and a reduction in the average parking time are observed after Paid Parking Zones (PPZ) introduction.. One of the factors influencing the functioning of PPZ is efficient traffic management in the area of PPZ based on reliable traffic measurements and analysis of parking characteristics. The parking characteristics vary with time, i.e. during the day, week, month, and year. The variability of parking characteristics is influenced by many factors, i.a.: the location of parking spaces, the presence of a parking fee and its amount, providing drivers with information about empty parking spaces, etc. The article aimed to analyze the variability of parking characteristics in a weekly schedule under the operating conditions of PPZ and Dynamic Parking Information (DPI). The conducted statistical tests show that the distribution of the value of the use of parking space and the rotation indicator differ between working days and weekend days. In the case of the distribution of the value of the use of parking space between working days, there are no statistical differences, while the distribution of the rotation indicator differs statistically on particular working days. The analysis was performed as a part of research work entitled "Analysis of parking characteristics in the conditions of SPP and DIP functioning in selected areas of GZM cities".
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".