Bibliographic record
Abstract
CERN's John Osborne (TS) at the start of the 10 km with more than 1700 other runners. Good luck to the CERN runners in the forthcoming stages! CERN hosted the first stage of the 10th Tour du canton de Genève on the evening of Wednesday 26 May. The Tour du canton is an annual race run in four stages over four weeks, and this year started at CERN as part of the Golden Jubilee celebrations. The event attracted over 2000 runners, including over 40 from CERN, as well as a large crowd of onlookers. The 10.5 km route started and finished outside CERN's Main Building, taking in the Swiss countryside, crossing into France and coming back through the tunnel linking the two CERN sites. CERN runners finished in second place in the Enterprise category just 13 seconds behind Rolex S.A., setting up an exciting contest for the remaining stages at Bernex, Meyrin and Jussy.Results are on the Tour du canton website.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.683 | 0.487 |
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".