Methodologies for estimating and characterizing truck volumes on rural highways
Why this work is in the frame
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Bibliographic record
Abstract
The research develops and applies methodologies and new information systems for estimating and charactezing truck volumes on Manitoba highways.Monitoring and understanding truck volumes is critical for highway planning, design, and management functions.The thesis provides a systematic analysis of truck volumes using truck data developed through the period 1993 to 2003 inclusive for Manitoba provincial highways.It develops methods and related criteria for screening and editing truck data, and creates a detailed understanding of annual average daily truck traffic (AADTT), temporal variations, and classification mix of truck volumes.A subsystem of the University of Manitoba Transport lnformation Group (UMTIG)- Manitoba Truck Planning Network (Tang, Minty and Han, 2003) is developed and uniquely segmented for purposes of truck volume estimation and characterizatjon for the year 2002.Three methods are developed and applied for the estimation of truck volumes: (l) direct measurement method; (2) transferring method; and (3) base Manitoba truck volume method.Truck volumes on different highway segments arc charaterized, by temporal variations and classification mix through the assignment of control stations and truck traffic pattern groups developed in this research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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