The application of METRO model to the Czech road data – preliminary results
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
The goal of this paper is to adopt the METRo model to Czech road data and to present the first experiences. The METRo, a physically based model developed by the Meteorological Service of Canada, produces a 30-hours forecast of road conditions and its temperature. The METRo requires measurements from the road weather stations and forecasts of a numerical weather prediction model as an input data. This first test was performed with road data for the Svojkovice station located at 70.3 km of the motorway D5 (Prague-Plzeň) and the ALADIN-CZ NWP model forecasts were used. The test was performed for data from the winter 2009/2010. The forecasted surface temperature yielded higher values comparing to the measured ones during the daytime and lower values during the night time. These differences were more pronounced when considering the beginning (October) and the end (March) of the winter season only as a probable impact of high insolation. The accuracy of the forecasted road conditions expressed by the code specifying road conditions ranged between 65 and 80% for all lead times of the forecasts.
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 | 0.001 | 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