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Record W1509249164 · doi:10.1051/0004-6361/201425455

Deep SDSS optical spectroscopy of distant halo stars

2015· article· en· W1509249164 on OpenAlexfundno aff
Emma Fernández-Alvar, Carlos Allende Prieto, Katharine J. Schlesinger, Timothy C. Beers, A. C. Robin, Donald P. Schneider, Young Sun Lee, Dmitry Bizyaev, Garrett Ebelke, Elena Malanushenko, Viktor Malanushenko, D. Oravetz, Kaike Pan, Audrey Simmons

Bibliographic record

VenueAstronomy and Astrophysics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryUniversité de Franche-ComtéChungnam National UniversityAgence Nationale de la RechercheYork UniversityJoint Institute for Nuclear Astrophysics - Center for the Evolution of the ElementsOffice of ScienceJohns Hopkins UniversityCarnegie Mellon UniversityCollege of Engineering, Michigan State UniversityHarvard UniversityOhio State UniversityNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsAstrophysicsHaloStarsPhysicsMilky WaySkySpectral lineSpectroscopyGalaxyAstronomy

Abstract

fetched live from OpenAlex

Aims. We analyze a sample of 3944 low-resolution (R ~ 2000) optical spectra from the Sloan Digital Sky Survey (SDSS), focusing on stars with effective temperatures 5800 ≤ Teff ≤ 6300 K, and distances from the Milky Way plane in excess of 5 kpc, and determine their abundances of Fe, Ca, and Mg.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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
Published2015
Admission routes1
Has abstractyes

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