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Record W4297676375 · doi:10.1051/0004-6361/201321326

The AMIGA sample of isolated galaxies

2013· article· en· W4297676375 on OpenAlexfundno aff
M. Argudo–Fernández, S. Verley, G. Bergond, J. W. Sulentic, J. Sabater, M. Fernández Lorenzo, S. Léon, D. Espada, L. Verdes‐Montenegro, J. D. Santander-Vela, José Enrique Ruiz, S. Sánchez–Expósito

Bibliographic record

VenueAstronomy and Astrophysics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryBrookhaven National LaboratoryScience and Technology Facilities CouncilPrinceton UniversityAlfred P. Sloan FoundationUniversity of WashingtonJohns Hopkins UniversityCollege of Engineering, Michigan State UniversitySeventh Framework ProgrammeInstituto de Astrofísica de CanariasMinisterio de Ciencia e InnovaciónMinisterio de Economía y CompetitividadYork UniversityUniversity of ArizonaOffice of ScienceOhio State UniversityJunta de AndalucíaNew Mexico State UniversityUniversity of PortsmouthYale UniversityVanderbilt UniversityNational Science FoundationU.S. Department of EnergyCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationJet Propulsion Laboratory
KeywordsGalaxyAstrophysicsSkyContext (archaeology)PhysicsInterstellar mediumSample (material)AstronomyGeography

Abstract

fetched live from OpenAlex

Context. To understand the evolution of galaxies, it is necessary to have a reference sample where the effect of the environment is minimized and quantified. In the framework of the AMIGA project (Analysis of the interstellar Medium of Isolated GAlaxies), we present a revision of the environment for galaxies in the Catalogue of Isolated Galaxies (CIG, Karachentseva 1973, Astrof. Issledovaniia Byu. Spec. Ast. Obs., 8, 3) using the ninth data release of the Sloan Digital Sky Survey (SDSS-DR9).

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.181
Teacher spread0.177 · 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

Citations43
Published2013
Admission routes1
Has abstractyes

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