Bibliographic record
Abstract
The local winners of the global particle physics Photowalk have been announced by the five participating laboratories. At CERN, Diego Giol and Christian Stephani were the jury’s favourites, and their photos will now go forward to the global vote, competing against the local winners from DESY in Germany, Fermilab in the US, KEK in Japan and TRIUMF in Canada. Two prizes are to be awarded, one selected by a global jury, the other by popular vote – it’s time to get voting! Diego Giol #1 The global winners of the Photowalk contest will be revealed by the second week of October, but the local CERN winners were announced last week. After three weeks of work, two meetings of the jury and three successive selections, 20 photos were chosen from the 792 entries. The three highest-ranked will participate in the final competition. The public can vote for their favourite photos on the interactions.org website until 8 October. Only two photographers took the three winning photos at CERN: Argentinian Diego Giol, who contributed twice, and Swiss Christian Stephani. Giol, a software engineer, moved to Switzerland a few years ago, and currently works as a project manager at ISO in Geneva. He has been especially passionate about technology and, of course, photography since a young age. Stephani, born in Biel, is currently a student at Biel School of Visual Arts, and has been interested in the arts and photography since 2002. Christian Stefani The CERN jury was composed of five members: a professional photographer, the CERN photographer, a computer scientist, a representative of the CERN Library, and a member of the Physics Department. “The theme of the CERN contest was ‘a different view of CERN’, so, when selecting the photos, we gave preference to those with a novelty aspect”, says Maximilien Brice, CERN photographer and a member of the jury. “The selection was hard, though, as the level was quite high despite it being an amateur contest. I was really impressed by the quality of the photographs as well as by the equipment used by the contestants.” “Beside the technical aspect, the selection took into account also the human and emotional sides since an important quality of a photo is the telling of a story”, adds Michael Doser, SME group leader and the Physics Department's representative on the jury. Diego Giol #2 The twenty finalist entries of the CERN contest will be exhibited at the Globe next year. A gallery of all the photos taken at the five laboratories is available on Photowalk’s flickr website. For futher information, see the Bulletin's previous article : Beauty is in the eye of the photographer.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.587 | 0.403 |
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".