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Record W4292892878 · doi:10.1051/0004-6361/201424790

<i>Planck</i>intermediate results

2015· article· en· W4292892878 on OpenAlexaff
N. Aghanim, B. Altieri, M. Arnaud, M. Ashdown, J. Aumont, C. Baccigalupi, A. J. Banday, R. B. Barreiro, N. Bartolo, E. Battaner, A. Beelen, K. Benabed, A. Benoit-Lévy, J.-P. Bernard, M. Bersanelli, M. Béthermin, P. Bielewicz, L. Bonavera, J. R. Bond, J. Borrill, F. R. Bouchet, F. Boulanger, C. Burigana, E. Calabrese, R. Cañameras, J.-F. Cardoso, A. Catalano, A. Chamballu, Ranga‐Ram Chary, H. C. Chiang, P. R. Christensen, D. L. Clements, S. Colombi, F. Couchot, B. P. Crill, A. Curto, L. Danese, K. Dassas, R. D. Davies, Roger J. Davis, P. de Bernardis, A. de Rosa, G. de Zotti, J. M. Diego, H. Dole, S. Donzelli, O. Doré, M. Douspis, A. Ducout, X. Dupac, G. Efstathiou, F. Elsner, T. A. Enßlin, E. Falgarone, I. Flores-Cacho, O. Forni, M. Frailis, A. A. Fraisse, E. Franceschi, A. Frejsel, Brenda Frye, S. Galeotta, S. Galli, K. Ganga, M. Giard, E. Gjerløw, J. González-Nuevo, K. M. Górski, A. Gregorio, A. Gruppuso, David Guery, F. K. Hansen, D. Hanson, D. L. Harrison, G. Hélou, C. Hernández-Monteagudo, S. R. Hildebrandt, E. Hivon, W. A. Holmes, W. Hovest, K. M. Huffenberger, G. Hurier, A. H. Jaffe, T. R. Jaffe, E. Keihänen, R. Keskitalo, T. S. Kisner, R. Kneißl, J. Knoche, M. Kunz, H. Kurki‐Suonio, G. Lagache, J.-M. Lamarre, A. Lasenby, M. Lattanzi, C. R. Lawrence, E. Le Floc’h, R. Leonardi, F. Levrier, M. Liguori, P. B. Lilje, M. Linden-Vørnle, M. López-Caniego, P. M. Lubin, J. F. Macías–Pérez, T. Mackenzie, B. Maffei, N. Mandolesi, M. Maris, P. G. Martin, C. Martinache, E. Martínez-González, S. Masi, S. Matarrese, P. Mazzotta, A. Melchiorri, A. Mennella, M. Migliaccio, A. Moneti, L. Montier, G. Morgante, D. Mortlock, D. Munshi, J. A. Murphy, P. Natoli, M. Negrello, N. P. H. Nesvadba, D. Novikov, I. Novikov, A. Omont, L. Pagano, F. Pajot, F. Pasian, O. Perdereau, L. Perotto, F. Perrotta, V. Pettorino, F. Piacentini, M. Piat, S. Plaszczynski, É. Pointecouteau, G. Polenta, L. Popa, G. W. Pratt, S. Prunet, J.‐L. Puget, J. P. Rachen, W. T. Reach, M. Reinecke, M. Remazeilles, C. Renault, I. Ristorcelli, G. Rocha, G. Roudier, B. Rusholme, M. Sandri, D. Santos, G. Savini, D. Scott, L. D. Spencer, V. Stolyarov, R. Sunyaev, D. Sutton, J.-F. Sygnet, J. A. Tauber, L. Terenzi, L. Toffolatti, M. Tomasi, M. Tristram, G. Umana, L. Valenziano, J. Väliviita, I. Valtchanov, B. Van Tent, J. D. Vieira, P. Vielva, L. A. Wade, B. D. Wandelt, I. K. Wehus, N. Welikala, A. Zacchei, A. Zonca

Bibliographic record

VenueAstronomy and Astrophysics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
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 SuperiorMinisterio de Ciencia e InnovaciónCentre National de la Recherche ScientifiqueNational Aeronautics and Space AdministrationChina Scholarship CouncilScience and Technology Facilities CouncilTekesAgence Nationale de la RechercheNederlandse Organisatie voor Wetenschappelijk OnderzoekJet Propulsion LaboratoryCentre National d’Etudes SpatialesPartnership for Advanced Computing in Europe AISBLCalifornia Institute of TechnologyMax-Planck-GesellschaftUK Space AgencyScience Foundation Ireland
KeywordsPhysicsPlanckAstrophysicsAstronomy

Abstract

fetched live from OpenAlex

We have used the Planck all-sky submillimetre and millimetre maps to search for rare sources distinguished by extreme brightness, a few hundred millijanskies, and their potential for being situated at high redshift. These “cold” Planck sources, selected using the High Frequency Instrument (HFI) directly from the maps and from the Planck Catalogue of Compact Sources (PCCS), all satisfy the criterion of having their rest-frame far-infrared peak redshifted to the frequency range 353–857 GHz. This colour-selection favours galaxies in the redshift range z = 2–4, which we consider as cold peaks in the cosmic infrared background. With a beam at the four highest frequencies, our sample is expected to include overdensities of galaxies in groups or clusters, lensed galaxies, and chance line-of-sight projections. We perform a dedicated Herschel-SPIRE follow-up of 234 such Planck targets, finding a significant excess of red 350 and 500μm sources, in comparison to reference SPIRE fields. About 94% of the SPIRE sources in the Planck fields are consistent with being overdensities of galaxies peaking at 350μm, with 3% peaking at 500μm, and none peaking at 250μm. About 3% are candidate lensed systems, all 12 of which have secure spectroscopic confirmations, placing them at redshifts z> 2.2. Only four targets are Galactic cirrus, yielding a success rate in our search strategy for identifying extragalactic sources within the Planck beam of better than 98%. The galaxy overdensities are detected with high significance, half of the sample showing statistical significance above 10σ. The SPIRE photometric redshifts of galaxies in overdensities suggest a peak at z ≃ 2, assuming a single common dust temperature for the sources of Td = 35 K. Under this assumption, we derive an infrared (IR) luminosity for each SPIRE source of about 4 × 1012L⊙, yielding star formation rates of typically 700 M⊙ yr-1. If the observed overdensities are actual gravitationally-bound structures, the total IR luminosity of all their SPIRE-detected sources peaks at 4 × 1013L⊙, leading to total star formation rates of perhaps 7 × 103M⊙ yr-1 per overdensity. Taken together, these sources show the signatures of high-z (z> 2) protoclusters of intensively star-forming galaxies. All these observations confirm the uniqueness of our sample compared to reference samples and demonstrate the ability of the all-skyPlanck-HFI cold sources to select populations of cosmological and astrophysical interest for structure formation studies.

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)0.005
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0970.074

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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".

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Citations94
Published2015
Admission routes1
Has abstractyes

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