Arctic Geospatial Data for Cold Region Transportation Infrastructure Analysis: High-Resolution LiDAR Point Clouds along the Steese Highway, Alaska, January 2024-Site_4
Why this work is in the frame
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Bibliographic record
Abstract
Remote sensing makes it possible to gather data rapidly, accurately, and non-destructively, allowing for access to remote areas in near real-time. LiDAR sensor data were collected on previous test sites that were tested during the summer 2023 field study exercise on Alaska's Steese Highway, as part of continued efforts to provide more geospatial data in Arctic regions relevant to cold region research. The Steese Highway is a major highway connecting the city of Fairbanks, Alaska, to the small town of Circle, Alaska, near the Yukon River. The Steese Highway spans approximately 261 kilometers and is the only means of transportation for goods and supplies to the remote towns of both Central and Circle Alaska. The survey was conducted in January 2024 as a companion comparative dataset to the summer 2023 LiDAR dataset. The corresponding point cloud data shows evidence of road degradation and snow accumulation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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