UTILISATION OF FIVE- AND SIX-AXLE TRACTOR SEMITRAILERS IN WESTERN CANADA.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Analysis of trends in truck fleet mix and the relative productivity and operational characteristics of the five– and six–axle tractor–semi–trailers (342 and 3–S3) are presented. Marked increases in the use of 3–S3 at the expense of the 3–S2 are observed. The percentage of 342 in the heavy truck fleet dropped from about 70% in 1991 to about 50% in 1994, while the percentage of 343 increased from 9% and 20% over the same period. These changes could be explained by: better operating efficiency measured by the potential pavement damage per unit payload; flexible payload handling capability; and higher productivity indicated by the potential payload capacity actually utilised. Current trends in fleet mix changes suggest that the rate of increase in the percentage of 343 in the truck fleet is likely to be maintained in the next few years. Possible implications for trucks operations under North American Free Trade Agreement is that the 3–S3 offers a clear productivity advantage over the 3–52 and therefore suitable for long haul operations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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