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Sensitivity Modeling for LiteBIRD
Takashi Hasebe, P. A. R. Ade, Alexandre Adler, Erwan Allys, David Alonso, Kam Arnold, D. Auguste, J. Aumont, R. Aurlien, Jason Austermann, S. Azzoni, C. Baccigalupi, A. J. Banday, R. Banerji, R. B. Barreiro, N. Bartolo, S. Basak, E. S. Battistelli, Inmaculada Bautista, James A. Beall, D. Beck, S. Beckman, K. Benabed, Juan Bermejo-Ballesteros, M. Bersanelli, J. Bonis, J. Borrill, F. R. Bouchet, F. Boulanger, Sophie Bounissou, M. Brilenkov, Michael D. Brown, M. Bucher, E. Calabrese, M. Calvo, P. Campeti, A. Carones, F. J. Casas, A. Catalano, A. Challinor, V. Chan, K. Cheung, Y. Chinone, J. F. Cliche, F. Columbro, William R. Coulton, Javier Cubas, A. Cukierman, D. Curtis, G D'alessandro, K. Dachlythra, P. de Bernardis, T. de Haan, E. de la Hoz, M. De Petris, S. Della Torre, C. Dickinson, P. Diego-Palazuelos, M. Dobbs, Tadayasu Dotani, D. Douillet, L. Duband, A. Ducout, Shannon M. Duff, J. M. Duval, Ken Ebisawa, T. Elleflot, H. K. Eriksen, Josquin Errard, Thomas Essinger-Hileman, F. Finelli⋆, Raphael Flauger, C. Franceschet, U. Fuskeland, S. Galli, M. Galloway, K. Ganga, J. R. Gao, R. T. Génova-Santos, M. Gerbino, M. Gervasi, T. Ghigna, S. Giardiello, E. Gjerløw, M. L. Gradziel, J. Grain, L. Grandsire, F. Grupp, A. Gruppuso, J. E. Gudmundsson, N. W. Halverson, J.–Ch. Hamilton, Peter Hargrave, M. Hasegawa, M. Hattori, M. Hazumi, S. Henrot–Versillé, L. T. Hergt, D. Herman, D. Herranz, C. A. Hill, Gene C. Hilton, E. Hivon, Renée Hložek, D. Hoang, Amber Hornsby, Yurika Hoshino, Johannes Hubmayr, Kiyotomo Ichiki, Teruhito Iida, Hiroaki Imada, Kosei Ishimura, H. Ishino, G. Jaehnig, M. Jones, Tooru Kaga, Shingo Kashima, N. Katayama, A. Kato, T. Kawasaki, Brian Keating, T. Kisner, Yohei Kobayashi, Nozomu KOGISO, A. Kogut, Kazunori Kohri, Eiichiro Komatsu, Kunimoto Komatsu, Kuniaki Konishi, N. Krachmalnicoff, I. Kreykenbohm, C. L. Kuo, A. Kushino, L. Lamagna, J. Van Lanen, G. Laquaniello, M. Lattanzi, A. T. Lee, C. Leloup, F. Levrier, E. Linder, Thibaut Louis, G. Luzzi, J. F. Macías–Pérez, T. Maciaszek, B. Maffei, D. Maino, M. Maki, S. Mandelli, M. Maris, E. Martínez-González, S. Masi, M. Massa, S. Matarrese, Frederick Matsuda, T. Matsumura, L. Mele, A. Mennella, M. Migliaccio, Y. Minami, Kazuhisa Mitsuda, A. Moggi, A. Monfardini, J. Montgomery, L. Montier, G. Morgante, B. Mot, Yasuhiro Murata, J. A. Murphy, M. Nagai, Y. Nagano, T. Nagasaki, Ryo Nagata, Shogo Nakamura, Ryo Nakano, Toshiya Namikawa, F. Nati, P. Natoli, S. Nerval, Toshiyuki Nishibori, H. Nishino, F. Noviello, C. O’Sullivan, Kimihide Odagiri, Hideaki Ogawa, S. Oguri, Hiroyuki Ohsaki, I. Ohta, Nozomi Okada, L. Pagano, A. Paiella, D. Paoletti, A. Passerini, G. Patanchon, V. Pelgrim, J. Peloton, F. Piacentini, M. Piat, G. Pisano, G. Polenta, D. Poletti, T. Prouvé, Giuseppe Puglisi, D. Rambaud, C. Raum, S. Realini, M. Reinecke, M. Remazeilles, A. Ritacco, G. Roudil, J. A. Rubiño-Martín, Michael Russell, H. Sakurai, Y. Sakurai, M. Sandri, Misao Sasaki, G. Savini, D. Scott, Joseph Seibert, Yutaro Sekímoto, B. D. Sherwin, Keisuke Shinozaki, Maresuke Shiraishi, Peter Shirron, G. Signorelli, Graeme Smecher, F. Spinella, S. L. Stever, R. Stompor, S. Sugiyama, R. M. Sullivan, Aritoki Suzuki, J. Suzuki, T. L. Svalheim, Eric R. Switzer, R. Takaku, Hayato Takakura, S. Takakura, Yusuke Takase, Youichi Takeda, A. Tartari, D. Tavagnacco, Angela C. Taylor, Ellen Taylor, K. Terao, J.-P. Thermeau, H. Thommesen, K. L. Thompson, B. Thorne, Takayuki Toda, M. Tomasi, M. Tominaga, N. Trappe, M. Tristram, M. Tsuji, Masahiro Tsujimoto, C. Tucker, J. Ullom, L. Vacher, G. Vermeulen, P. Vielva, F. Villa, Michael Vissers, N. Vittorio, B. D. Wandelt, W. Wang, Kazuya Watanuki, I. K. Wehus, J. Weller, Benjamin Westbrook, J. Wilms, B. Winter, Edward J. Wollack, Noriko Y. Yamasaki, T. Yoshida, J. Yumoto, A. Zacchei, M. Zannoni, A. Zonca
Bibliographic record
VenueJournal of Low Temperature Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersScience and Technology Facilities Council
KeywordsCosmic microwave backgroundPhysicsTransition edge sensorDetectorOpticsNoise (video)Sensitivity (control systems)BolometerCosmic background radiationMicrowavePolarization (electrochemistry)Radiation
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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.029
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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 designSimulation or modeling
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
Citations5
Published2022
Admission routes1
Has abstractno