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The IceProd framework: Distributed data processing for the IceCube neutrino observatory
M. G. Aartsen, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, D. Altmann, C. Argüelles, J. Auffenberg, X. Bai, M. D. Baker, S. W. Barwick, V. Baum, R. Bay, J. J. Beatty, J. Becker Tjus, K.-H. Becker, S. BenZvi, P. Berghaus, D. Berley, E. Bernardini, A. Bernhard, Dominique Besson, G. Binder, D. Bindig, M. Bissok, E. Blaufuss, J. Blumenthal, D. J. Boersma, C. Böhm, D. Bose, S. Böser, O. Botner, L. Brayeur, H.-P. Bretz, A. M. Brown, R. Bruijn, J. Casey, M. Casier, D. Chirkin, A. Christov, B. Christy, K. Clark, Lew Classen, F. Clevermann, S. Coenders, S. Cohen, D. F. Cowen, A.H. Cruz Silva, M. Danninger, J. Daughhetee, J. C. Davis, M. Day, C. De Clercq, S. De Ridder, P. Desiati, K. D. de Vries, M. de With, T. DeYoung, J. C. Díaz–Vélez, M. Dunkman, R. Eagan, B. Eberhardt, B. Eichmann, J. Eisch, S. Euler, P. A. Evenson, O. Fadiran, A. R. Fazely, Anatoli Fedynitch, J. Feintzeig, T. Feusels, K. Filimonov, C. Finley, T. Fischer-Wasels, S. Flis, A. Franckowiak, K. Frantzen, T. Fuchs, T. K. Gaisser, J. S. Gallagher, L. Gerhardt, L. Gladstone, T. Glüsenkamp, A. Goldschmidt, G. Golup, J.G. Gonzalez, J. A. Goodman, D. Góra, D. T. Grandmont, D. Grant, P. Gretskov, J. C. Groh, A. Groß, C. Ha, A. Haj Ismail, P. Hallen, A. Hallgren, F. Halzen, K. Hanson, D. Hebecker, D. Heereman, D. Heinen, K. Helbing, R. Hellauer, S. Hickford, G. C. Hill, K. D. Hoffman, R. Hoffmann, A. Homeier, K. Hoshina, F. Huang, W. Huelsnitz, P. O. Hulth, K. Hultqvist, S. Hussain, A. Ishihara, E. Jacobi, J. Jacobsen, K. Jagielski, G. S. Japaridze, K. Jero, O. Jlelati, B. Kaminsky, A. Kappes, T. Karg, A. Karle, M. Kauer, J. L. Kelley, J. Kiryluk, J. Kläs, J.-H. Köhne, G. Kohnen, H. Kolanoski, L. Köpke, Claudio Kopper, S. Kopper, D. J. Koskinen, M. Kowalski, M. Krasberg, A. Kriesten, K. Krings, G. Kroll, J. Kunnen, N. Kurahashi, T. Kuwabara, M. Labare, H. Landsman, M. J. Larson, M. Lesiak-Bzdak, M. Leuermann, J. Leute, J. Lünemann, Oscar Macías, J. Madsen, G. Maggi, R. Maruyama, K. Mase, H. S. Matis, F. McNally, K. Meagher, M. Merck, G. Merino, T. Meures, S. Miarecki, E. Middell, N. Milke, J. Miller, L. Mohrmann, T. Montaruli, R. Morse, R. Nahnhauer, Uwe Naumann, Hans Niederhausen, Sarah Nowicki, D. R. Nygren, A. Obertacke, S. Odrowski, A. Olivas, A. Omairat, A. O’Murchadha, L. Paul, Joshua Pepper, C. Pérez de los Heros, C. Pfendner, D. Pieloth, E. Pinat, J. Posselt, P. B. Price, G. T. Przybylski, M. Quinnan, L. Rädel, Ian Rae, M. Rameez, K. Rawlins, P. Redl, R. Reimann, E. Resconi, W. Rhode, M. Ribordy, M. Richman, Benedikt Riedel, J. P. Rodrigues, C. Rott, T. Ruhe, B. Ruzybayev, D. Ryckbosch, S. M. Saba, H. G. Sander, M. Santander, S. Sarkar, K. Schatto, F. Scheriau, T. Schmidt, M. Schmitz, S. Schoenen, S. Schöneberg, A. Schönwald, A. Schukraft, L. Schulte, David Schultz, O. Schulz, D. Seckel, Y. Sestayo, S. Seunarine, R. Shanidze, C. Sheremata, M.W.E. Smith, Dennis Soldin, G. M. Spiczak, Christian Spiering, M. Stamatikos, Todor Stanev, N. A. Stanisha, A. Stasik, T. Stezelberger, R. G. Stokstad, A. Stößl, E. A. Strahler, L. R. Strom, N. L. Strotjohann, G. W. Sullivan, H. Taavola, I. Taboada, A. Tamburro, A. Tepe, S. Ter–Antonyan, G. Tešić, S. Tilav, P. A. Toale, M. N. Tobin, S. Toscano, M. Tselengidou, E. Unger, M. Usner, S. Vallecorsa, N. van Eijndhoven, A. Van Overloop, J. V. Santen, M. Vehring, M. Vöge, M. Vraeghe, C. Walck, T. Waldenmaier, M. Wallraff, Ch. Weaver, M. Wellons, Chris Wendt, S. Westerhoff, N. Whitehorn, K. Wiebe, C. H. Wiebusch, D. R. Williams, H. Wissing, M. Wolf, T. R. Wood, K. Woschnagg, Dawei Xu, Xiaolin Xu, G. Yodh, S. Yoshida, P. Zarzhitsky, J. Ziemann, Simon Zierke, M. Zoll
Bibliographic record
VenueJournal of Parallel and Distributed Computing · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of TorontoUniversity of Alberta
FundersOffice of Polar ProgramsJapan Society for the Promotion of ScienceScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaKnut och Alice Wallenbergs StiftelseNational Research Foundation of KoreaFonds Wetenschappelijk OnderzoekMarsden FundBundesministerium für Bildung und ForschungDivision of PhysicsHelmholtz Alliance for Astroparticle PhysicsRuhr-Universität BochumDanmarks GrundforskningsfondNational Science FoundationBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftNational Research FoundationAustralian Research CouncilWestern Canada Research GridUniversity of OxfordVlaamse regeringFonds De La Recherche Scientifique - FNRSPolarforskningssekretariatetCompute CanadaU.S. Department of EnergyUniversity of Wisconsin-MadisonVetenskapsrådetWisconsin Alumni Research FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPython (programming language)NeutrinoComputer sciencePlug-inDetectorPhysicsMiddleware (distributed applications)XMLData processingDatabaseGrid computingDark matterOperating systemCosmic rayGridParticle physicsAstronomy
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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.052
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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 head0.029
GPT teacher head0.275
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreSoftware
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
Citations15
Published2014
Admission routes2
Has abstractno