International Conference on Computing in High Energy and Nuclear Physics (CHEP'09)
Bibliographic record
Abstract
The 17th International Conference on Computing in High Energy and Nuclear Physics (CHEP) was held on 21–27 March 2009 in Prague, Czech Republic. CHEP is a major series of international conferences for physicists and computing professionals from the worldwide High Energy and Nuclear Physics community, Computer Science, and Information Technology. The CHEP conference provides an international forum to exchange information on computing experience and needs for the community, and to review recent, ongoing and future activities. Recent conferences were held in Victoria, Canada 2007, Mumbai, India in 2006, Interlaken, Switzerland in 2004, San Diego, USA in 2003, Beijing, China in 2001, Padua, Italy in 2000. The CHEP'09 conference had 600 attendees with a program that included plenary sessions of invited oral presentations, a number of parallel sessions comprising 200 oral and 300 poster presentations, and an industrial exhibition. We thanks all the presenters, for the excellent scientific content of their contributions to the conference. Conference tracks covered topics on Online Computing, Event Processing, Software Components, Tools and Databases, Hardware and Computing Fabrics, Grid Middleware and Networking Technologies, Distributed Processing and Analysis and Collaborative Tools. The conference included excursions to Prague and other Czech cities and castles and a banquet held at the Zofin palace in Prague. The next CHEP conference will be held in Taipei, Taiwan on 18–22 October 2010. We would like thank the Ministry of Education Youth and Sports of the Czech Republic and the EU ACEOLE project for the conference support, further to commercial sponsors, the International Advisory Committee, the Local Organizing Committee members representing the five collaborating Czech institutions Jan Gruntorad (co-chair), CESNET, z.s.p.o., Prague Andrej Kugler, Nuclear Physics Institute AS CR v.v.i., Rez Rupert Leitner, Charles University in Prague, Faculty of Mathematics and Physics Milos Lokajicek (co-chair), Institute of Physics AS CR, v.v.i., Prague Vojtech Petracek, Czech Technical University in Prague, Faculty of Nuclear Sciences and Physical Engineering and especially the Programme Committee for their careful choice of conference contributions and their enormous work with organization of 340 post conference proceedings paper review Ludek Matyska (chair), CESNET Online Computing Volker Gülzow, DESY Jiri Masik, University of Manchester/on leave from Institute of Physics AS CR, Prague Event Processing Elizabeth Sexton-Kennedy, FNAL Tomas Davidek, Charles University, Prague Software Components, Tools and Databases Paolo Calafiura, LBNL Julius Hrivnac, LAL Track 4 Hardware and Computing Fabrics Takashi Sasaki, KEK Jiri Chudoba, Institute of Physics AS CR, Prague Grid Middleware and Networking Technologies Francesco Giacomini, CERN Ales Krenek, Masaryk University, Brno/CESNET Distributed Processing and Analysis Latchezar Betev, CERN Simon Lin, ASGC, Taipei Dagmar Adamova, Nuclear Physics Institute AS CR, Prague Collaborative Tools Eva Hladka, Masaryk University, Brno/CESNET Thank you to all who made CHEP'09 a success. Jan Gruntorad and Milos Lokajicek CHEP'09 Conference Chairs Prague, March 2010 The PDF and HTML files contain a list of all CHEP'09 contributions.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.120 | 0.071 |
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".