Wearing Surface Testing: Yukon River Bridge
Bibliographic record
Abstract
The Yukon River Bridge, also known as the E.L. Patton Bridge, carries the twolane Dalton Highway and the trans-Alaska oil pipeline across the Yukon River at a 6% grade.It is 30 feet wide, with 6 spans; it was designed to withstand -60 degrees Fahrenheit temperatures, huge ice loads from the river, truck loads hauling supplies to the oil fields, the oil pipeline, and, in the future, a gas line.Over 30 years, the timber decking has been replaced several times -in 1981, 1992, 1999, and 2007.The trees that produced the original decking were massive old-growth firs, strong and close-grained.Subsequent decking has come from younger trees, which produce softer wood.As timber quality has decreased, time between replacements has also decreased, while material costs increase.Every time the Yukon River Bridge deck is resurfaced, it costs the public millions of dollars.Further, in the past only timber was used, and the quality of this material is decreasing as the cost is increasing.It is imperative that new materials for use as a wearing surface for this bridge be identified.This research seeks to identify a material suitable for bridge decking that will last more than 15 years.A longer-lasting material will mean future savings to the ADOT&PF in the millions of dollars.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.009 |
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".