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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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.444
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 itQuick stats
Citations5
Published2022
Admission routes1
Has abstractno