De daling van het aantal verkeersdoden in 2004 nader geanalyseerd.
Bibliographic record
Abstract
Further analysis of the decrease in the number of road fatalities in 2004.\nThe numbers of road fatalities as well as the risk of dying in a road crash have been showing a downward trend. In 2004, the number of fatalities and the crash rate showed a relatively strong decline. In the present report the developments around the year 2004 are analysed and possible explanations for the extra reductions are searched for. This is not the first study of the developments around the year 2004. Previous studies indicated for which groups of road users the decline in fatalities was relatively large in 2004, gave a possible explanation for part of the decline, and ruled out a number of possible causes. However, these studies have not been able to make a statement about whether or not the decline is temporary and have not been able to explain the entire decline. For reliable forecasts it is important to know whether or not the decline was temporary and as data over a longer period and supplementary data have become available, this study once more analyses the developments around the year 2004.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".