CERN accelerator school: an introductory course in Poland
Bibliographic record
Abstract
For the first time since the CERN Accelerator School (CAS) was set up, the 'Introduction to Accelerator Physics' course was held in Zakopane, Poland. This course was organised together with the National Atomic Energy Agency, Warsaw, and the AGH University of Science and Technology, Cracow, and was held from 1-13 October 2006 at the foot of the Tatra Mountains. The course was very well attended with 113 participants representing 26 different nationalities. Although most of the participants originated from Europe, some students came from countries as far away as Canada, China, India and North America. The intensive programme comprised 35 lectures, 3 seminars given by local Polish lecturers, 5 tutorials where the students were split into four groups, a poster session where students could present their own work and 7 hours of guided and private study. The participants appreciated these study periods, which encouraged collaboration and knowledge-sharing in solving problems and gave them the opportunity to get to know each other better and establish useful contacts. In addition to the academic programme, the students had the opportunity during the traditional one-day excursion to visit the famous Wieliczka salt mines and the old town of Cracow. Feedback from the students after the course was very positive, praising the high standard of the lectures as well as the interesting and pleasant surroundings and excellent organization. The next CAS course will be a specialized course on Digital Signal Processing, which will take place in Sigtuna, Sweden, from 1-9 June 2007. Information can be found on the CAS web site: http://www.cern.ch/schools/CAS
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.085 | 0.065 |
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".