Some observations on BWIM data collected in Manitoba
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
Three highway bridges in the Canadian province of Manitoba are being monitored continuously not only for their long-term performance but also for bridge weighing-in-motion (BWIM). Data collected for the BWIM study has led to some observations that have far-reaching consequences about the design and evaluation loads for highway bridges. This paper presents the well-known concept of equivalent base length, B m , as a useful tool for comparing trucks with different axle weight and spacing configurations as they influence load effects in all bridges. It is discussed that the statistics of gross vehicle weights (GVWs), W, collected over a one-month period is not significantly different from that for the GVW data collected over a longer period. A rational method concludes that the value of W for the CL-W Truck, the design live load specified by the Canadian Highway Bridge Design Code, is 555 kN for Manitoba. The observed truck data in Manitoba presented on the W–B m space is found to be similar to that collected in the Canadian province of Ontario more than four decades ago. It was also found that the multi-presence factors, accounting for the presence of side-by-side trucks in two-lane bridges, specified in North American bridge design and evaluation codes are somewhat conservative.
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 | 0.001 | 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