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Record W4206681249 · doi:10.1093/mnras/stac078

Dark energy survey year 3 results: Cosmology with peaks using an emulator approach

2022· article· en· W4206681249 on OpenAlexaff
D. Zürcher, Janis Fluri, Raphaël Sgier, Tomasz Kacprzak, M. Gatti, C. Doux, L Whiteway, Alexandre Réfrégier, C. Chang, N Jeffrey, Bhuvnesh Jain, Pablo Lemos, David Bacon, A. Alarcon, A. Amon, K. Bechtol, M. R. Becker, G. M. Bernstein, A. Campos, R Chen, A. Choi, C. Davis, Joseph DeRose, Scott Dodelson, F. Elsner, J. Elvin-Poole, S. Everett, A. Ferté, D. Gruen, I. Harrison, Dragan Huterer, Mike Jarvis, P.-F. Léget, N. MacCrann, J. McCullough, J. Muir, J. Myles, A Navarro-Alsina, Shivam Pandey, J. Prat, Marco Raveri, R. P. Rollins, A. Roodman, C. Sánchez, L F Secco, E. Sheldon, T. Shin, M. A. Troxel, I. Tutusaus, B. Yin, M. Aguena, S. Allam, F. Andrade-Oliveira, J. Annis, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, R. Cawthon, Christopher J. Conselice, M. Costanzi, L. N. da Costa, M. E. S. Pereira, T. M. Davis, J. De Vicente, S. Desai, H. T. Diehl, J. P. Dietrich, P. Doel, K. Eckert, A. E. Evrard, I. Ferrero, B. Flaugher, P. Fosalba, D. N. Friedel, J. Frieman, J. García-Bellido, E. Gaztañaga, D. W. Gerdes, T. Giannantonio, R. A. Gruendl, J. Gschwend, G. Gutiérrez, S. R. Hinton, K. Honscheid, B. Hoyle, D. J. James, K. Kuehn, N. Kuropatkin, O. Lahav, C. Lidman, M. Lima, M. A. G. Maia, J. L. Marshall, P. Melchior, F. Menanteau, R. Miquel, R. Morgan, A. Palmese, F. Paz-Chinchón, A. Pieres, K. Reil, M Rodriguez Monroy, Kathy Romer, E. Sánchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Smith, E. Suchyta, G. Tarlé, D. Thomas, C. To, T N Varga, J. Weller, R. D. Wilkinson

Bibliographic record

VenuearXiv (Cornell University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsPerimeter Institute
FundersSLAC National Accelerator LaboratoryCentro de Investigaciones Energéticas, Medioambientales y TecnológicasDeutsche ForschungsgemeinschaftUniversity of EdinburghUniversity of Illinois at Urbana-ChampaignFinanciadora de Estudos e ProjetosUniversity of SussexUniversity of PennsylvaniaHigher Education Funding Council for EnglandUniversity of PortsmouthLawrence Berkeley National LaboratoryTexas A and M UniversityStanford UniversityUniversity of NottinghamScience and Technology Facilities CouncilUniversity College LondonUniversity of MichiganUniversity of ChicagoSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungOhio State UniversityArgonne National LaboratoryU.S. Department of Energy
KeywordsPhysicsCosmologyDark energyAstrophysicsAstronomyEnergy (signal processing)Observational cosmology

Abstract

fetched live from OpenAlex

Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, los autores pertenecientes a la UAM y el nombre del grupo de colaboración, si lo hubiere

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)0.003
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.055
GPT teacher head0.191
Teacher spread0.136 · 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 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

Citations72
Published2022
Admission routes1
Has abstractyes

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