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Record W4292233939 · doi:10.1051/0004-6361/201525818

<i>Planck</i>2015 results

2016· article· en· W4292233939 on OpenAlexaff
P. A. R. Ade, N. Aghanim, M. Ashdown, J. Aumont, C. Baccigalupi, M. Ballardini, A. J. Banday, R. B. Barreiro, N. Bartolo, S. Basak, P Battaglia, E. Battaner, K. Benabed, A. Benoı̂t, A. Benoit-Lévy, J.-P. Bernard, M. Bersanelli, P. Bielewicz, J. J. Bock, A. Bonaldi, L. Bonavera, J. R. Bond, J. Borrill, F. R. Bouchet, M. Bucher, C. Burigana, R. C. Butler, J.-F. Cardoso, G. Castex, A. Catalano, A. Chamballu, P. R. Christensen, S. Colombi, L. P. L. Colombo, B. P. Crill, A. Curto, F. Cuttaia, L. Danese, R. D. Davies, R. J. Davis, P. de Bernardis, A. de Rosa, G. de Zotti, J. Delabrouille, C. Dickinson, J. M. Diego, H. Dole, S. Donzelli, O. Doré, M. Douspis, A. Ducout, X. Dupac, G. Efstathiou, F. Elsner, T. A. Enßlin, H. K. Eriksen, J. Fergusson, F. Finelli⋆, O. Forni, M. Frailis, C. Franceschet, E. Franceschi, A. Frejsel, S. Galeotta, S. Galli, K. Ganga, M. Giard, Y. Giraud–Héraud, E. Gjerløw, J. González-Nuevo, K. M. Górski, S. Gratton, A. Gregorio, A. Gruppuso, F. K. Hansen, D. Hanson, D. L. Harrison, S. Henrot–Versillé, D. Herranz, S. R. Hildebrandt, E. Hivon, W. A. Holmes, A. Hornstrup, W. Hovest, K. M. Huffenberger, G. Hurier, A. H. Jaffe, T. R. Jaffe, M. Juvela, E. Keihänen, R. Keskitalo, K. Kiiveri, T. S. Kisner, J. Knoche, N. Krachmalnicoff, M. Kunz, H. Kurki‐Suonio, G. Lagache, A. Lähteenmäki, J.–M. Lamarre, A. Lasenby, M. Lattanzi, J. P. Leahy, R. Leonardi, J. Lesgourgues, F. Levrier, M. Liguori, P. B. Lilje, M. Linden-Vørnle, V. Lindholm, M. López-Caniego, P. M. Lubin, J. F. Macías–Pérez, G. Maggio, N. Mandolesi, A. Mangilli, M. Maris, P. G. Martin, E. Martínez-González, S. Masi, S. Matarrese, P. Mazzotta, P. McGehee, P. R. Meinhold, A. Melchiorri, L. Mendes, A. Mennella, M. Migliaccio, S. Mitra, L. Montier, G. Morgante, N. Morisset, D. Mortlock, A. Moss, D. Munshi, J. A. Murphy, P. Naselsky, F. Nati, P. Natoli, C. B. Netterfield, H. U. Nørgaard-Nielsen, D. Novikov, I. Novikov, Niels Oppermann, F. Paci, L. Pagano, D. Paoletti, B. Partridge, F. Pasian, G. Patanchon, T. J. Pearson, M. Peel, O. Perdereau, L. Perotto, F. Perrotta, V. Pettorino, F. Piacentini, E. Pierpaoli, D. Pietrobon, E. Pointecouteau, G. Polenta, G. W. Pratt, G. Prézeau, S. Prunet, J.-L. Puget, J. P. Rachen, R. Rébolo, M. Reinecke, M. Remazeilles, A. Renzi, G. Rocha, E. Romelli, C. Rosset, M. Rossetti, G. Roudier, J. A. Rubiño-Martín, B. Rusholme, M. Sandri, D. Santos, M. Savelainen, D. Scott, M. D. Seiffert, E. P. S. Shellard, L. D. Spencer, V. Stolyarov, D. Sutton, A.-S. Suur-Uski, J.-F. Sygnet, J. A. Tauber, D. Tavagnacco, L. Terenzi, L. Toffolatti, M. Tomasi, M. Tristram, J. Tuovinen, M. Türler, G. Umana, L. Valenziano, J. Väliviita, B. Van Tent, T. Vassallo, P. Vielva, F. Villa, L. A. Wade, B. D. Wandelt, R. A. Watson, I. K. Wehus, A. Wilkinson, D. Yvon, A. Zacchei, A. Zonca

Bibliographic record

VenueAstronomy and Astrophysics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsUniversity of British ColumbiaMcGill UniversityUniversity of Toronto
FundersFundação para a Ciência e a TecnologiaInstitut National de Physique Nucléaire et de Physique des ParticulesMinistério da Ciência, Tecnologia e Ensino SuperiorCentre National de la Recherche ScientifiqueNational Aeronautics and Space AdministrationChina Scholarship CouncilScience and Technology Facilities CouncilTekesCentre National d’Etudes SpatialesEuropean Space AgencyPartnership for Advanced Computing in Europe AISBLMax-Planck-GesellschaftUK Space AgencyScience Foundation Ireland
KeywordsPlanckPhysicsTimelinePipeline (software)AstrophysicsData processingAstronomyDatabaseStatisticsComputer science

Abstract

fetched live from OpenAlex

We present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. We refer to other related papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.

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 imitation

Not 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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0450.039

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine 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 designObservational
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

Citations85
Published2016
Admission routes1
Has abstractyes

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