The application of METRO model to the Czech road data – preliminary results
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.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".