Bridging the Generations: The Evolution of Metal Truss Bridges in Michigan
Bibliographic record
Abstract
As far back as I can remember old bridges have always fascinated me. I can remember being a little boy, perhaps only five years old, riding around in the car with my parents. Our family would frequently take pleasure drives around the area, just for fun. I would always get excited when we crossed some old bridge, and I often had childish nicknames for some of the bridges that we crossed often. I grew up near Port Huron Michigan, and so the original Blue Water Bridge, connecting Port Huron to Sarnia, Ontario was a favorite bridge of mine. However, I always liked the smaller bridges on local roads the most. I liked the bascule bridge in downtown Port Huron, with its ornate railings. The bridge would lift up to let boats pass under and travel down the Black River. When my family would go downtown to see the sailboats during the Port Mackinac to Mackinac race, I always enjoyed seeing this bridge. I also enjoyed other bridges around the area as a kid, including old concrete bridges, such as the Wadhams Road Bridge over the Pine River in St. Clair County, that many people probably do not give a second glance
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".