← Back to cohort
Silicon detectors for the sLHC
A. A. Affolder, A. N. Aleev, P. P. Allport, L. Andricek, M. Artuso, J.P. Balbuena, L.I. Barabash, T. Barber, A. Barcz, D. Bassignana, R. L. Bates, M. Battaglia, M. Beimforde, J. Bernardini, C. Betancourt, G. M. Bilei, D. Bisello, A. Blue, J. Böhm, G. Bolla, A. Borgia, L. Borrello, D. Bortoletto, M. Boscardin, Marten Bosma, T. J. V. Bowcock, M. Breindl, Jan Brož, M. Bruzzi, A. Brzozowski, P. Buhmann, C. M. Buttar, F. Campabadal, A. Candelori, G. Casse, S. Charron, D. Chren, S. Cihangir, V. Cindro, P. Collins, E. Cortina, C.A. Costinoaia, D. Creanza, Colon Cristobal, G.‐F. Dalla Betta, W. De Boer, M. De Palma, R. Demina, A. Dierlamm, Sergio Cañas Díez, D. Dobos, F. Doherty, I. Dolenc, Z. Doležal, A. P. Dolgolenko, Adrian Driewer, Suchandra Dutta, D. Eckstein, L. Eklund, I.V. Eremin, V. Eremin, J. Erfle, N. Fadeeva, M. Fahrer, F. Fiori, C. Fleta, E. Focardi, D. C. Forshaw, E. Fretwurst, Martin Frey, A. Bates, C. Gallrapp, C. Garcı́a, E. Gaubas, M. H. Genest, K. Giolo, M. Gläser, C. Goessling, А. А. Голубев, I. Gorelov, G. Grégoire, P. Gregori, E. Grigoriev, A. A. Grillo, S. Grinstein, A.A. Groza, J. Guskov, Thor-Erik Hansen, J. Härkönen, F.G. Hartjes, F. Hartmann, M. R. Hoeferkamp, R. Horisberger, A. Houdayer, D. Hynds, I. Ilyashenko, A. Junkes, A. Kadys, P. Kamiński, A. Karpenko, Katharina Kaska, N.M. Kazuchits, V. Kažukauskas, A. Kharchuk, V.I. Khivrich, J. Kierstead, R. Klanner, R. Klingenberg, E. Koffeman, Michael H. Köhler, Z. Kohout, S. Korjenevski, I. Korolkov, R. Kozłowski, M. Kozubal, G. Kramberger, S. Kühn, S. Kuleshov, Andrej Kuznetsov, S. Kwan, A. La Rosa, C. Lacasta, J. C. Lange, K. Lassila-Perini, V.F. Lastovetsky, I. Lazanu, S. Lazanu, C. Lebel, G. Lefeuvre, V. Lemaı̂tre, C. Leroy, Z. Li, G. Lindström, A. Litovchenko, П.Г. Литовченко, M. Lozano, Z. Łuczyński, P. Luukka, A. Macchiolo, A. Macraighne, T. Mäenpää, Л. Ф. Макаренко, I. Mandić, D. Maneuski, N. Manna, R. Marco, S. Martí-García, S. Marunko, Petr Mašek, Keith Mathieson, M. Matysek, Julien Mekki, A. Messineo, J. Metcalfe, M. Mikeštíková, M. Mikuž, O. Militaru, J. Miyamoto, M. Moll, E. Monokhov, R. Mori, H. G. Moser, D. Muenstermann, F. J. Muñoz Sánchez, A. S. Naletko, R. Nisius, V. OʼShea, N. Pacifico, D. Pantano, C. Parkes, U. Parzefall, D. Passeri, M. Pawłowski, G. Pellegrini, H. Pernegger, Marco Petasecca, C. Piemonte, G.U. Pignatel, Ioana Pintilie, L. Pintilie, K. Piotrzkowski, R. Placekett, Th. Pöhlsen, L.A. Polivtsev, J. Popule, S. Pospı́šil, Jens Preiss, V. Radicci, Roxana Radu, J.M. Raf, R. Rando, R. Richter, R.S. Roeder, R.S.M. Mary Roger, С. В. Рогожкин, T. Rohe, S. Ronchin, C. Rott, Amitava Roy, A. Rummler, A. Ruzin, H. F-W. Sadrozinski, S. Sakalauskas, Nino Samadashvili, M. Scaringella, B. A. Schumm, S. Seidel, A. Seiden, I. P. J. Shipsey, J. Sibille, P. Šı́cho, T. Slavíček, M. Solar, U. Soldevila-Serrano, Seunghee Son, V. Sopko, B. Sopko, N. Spencer, L. Spiegel, A. K. Srivastava, Georg Steinbrueck, Graeme A Stewart, D. Stolze, J. Storasta, B. Surma, B. G. Svensson, P. Tan, M. Tomášek, K. Toms, S. Tsiskaridze, A. I. Tsvetkov, Yu. V. Tubol’tsev, E. Tuominen, E. Tuovinen, T. Tuuva, M. Tylchin, H. Uebersee, M. Ullán, J.V. Vaitkus, M. van Beuzekom, E. Verbitskaya, Inmaculada Álvarez, J. Visser, J. H. Vossebeld, V. Vrba, Murray Walz, P. Weigell, L. A. M. Wiik, I. Wilhelm, R. Wunstorf, A. Zaluzhny, M. Zavrtanik, J. Żelazko, M. Zen, В. Жуков, D. Žontar, N. Zorzi
Bibliographic record
VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsUniversité de Montréal
FundersScience and Technology Facilities CouncilCERN
KeywordsLarge Hadron ColliderRadiation hardeningDetectorLuminosityPhysicsSiliconTracking (education)OptoelectronicsSemiconductor detectorRadiation damageRadiationIrradiationUpgradeSemiconductorColliderNuclear physicsOpticsAstrophysicsComputer science
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.371
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.111 | 0.035 |
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.
Opus teacher head0.098
GPT teacher head0.380
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation status
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.
The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical
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".
Quick stats
Citations25
Published2011
Admission routes1
Has abstractno