Evaluation of the Level of Service of “Vía Expresa Paseo de la República” (Peru): Canada - Javier Prado Section
Bibliographic record
Abstract
This research evaluates the level of service of one of the main roads in Lima (Peru), which is “Vía Expresa Paseo de la República”. Specifically, the section of this road between Canada and Javier Prado Avenues was evaluated. For this, the first step was to film the vehicular flow at both ends of the section studied, in order to obtain the number of vehicles that transited every certain period of time, which allows to measure the Traffic Flow (between 1,200 to 2,100 veh/h/lane). Then, the time taken by the vehicles to move a certain distance defined in the films was estimated, which allowed estimating, with a harmonic average, the Space Mean Speed (between 20 and 65 km/h). After that, using the Greenshields equation and the fundamental traffic equation, a regression algorithm in R language is used to identify the theoretical quadratic relationship between both measured variables and thus obtain the characteristics of the road, which are the Free-Flow Speed (between 70 to 90 km/h) and the Jam Density (between 85 to 110 veh/km). In this way, with the measured parameters, the HCM 2000 standard is used to know the level of service of the evaluated road, obtaining as a result an F level.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".