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Record W2914425456 · doi:10.1088/1538-3873/ab0075

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) Spectrographs

2019· article· en· W2914425456 on OpenAlexfundno aff

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratorySmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieBrookhaven National LaboratoryMinistério da Ciência, Tecnologia e InovaçãoUniversity of OxfordYork UniversityLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityUniversidad Nacional Autónoma de MéxicoCollege of Engineering, Michigan State UniversityPrinceton UniversityUniversity of WashingtonAlfred P. Sloan FoundationJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahHarvard UniversityOhio State UniversityU.S. Department of EnergySmithsonian InstitutionNational Science FoundationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityMax-Planck-Institut für Astrophysik
KeywordsSpectrographObservatoryTelescopeSkyLAMOSTMilky WayGalactic astronomySpectrometerWilliam Herschel Telescope

Abstract

fetched live from OpenAlex

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) Spectrographs, Wilson, J. C., Hearty, F. R., Skrutskie, M. F., Majewski, S. R., Holtzman, J. A., Eisenstein, D., Gunn, J., Blank, B., Henderson, C., Smee, S., Nelson, M., Nidever, D., Arns, J., Barkhouser, R., Barr, J., Beland, S., Bershady, M. A., Blanton, M. R., Brunner, S., Burton, A., Carey, L., Carr, M., Colque, J. P., Crane, J., Damke, G. J., Davidson, J. W., Dean, J., Di Mille, F., Don, K. W., Ebelke, G., Evans, M., Fitzgerald, G., Gillespie, B., Hall, M., Harding, A., Harding, P., Hammond, R., Hancock, D., Harrison, C., Hope, S., Horne, T., Karakla, J., Lam, C., Leger, F., MacDonald, N., Maseman, P., Matsunari, J., Melton, S., Mitcheltree, T., O’Brien, T., O’Connell, R. W., Patten, A., Richardson, W., Rieke, G., Rieke, M., Roman-Lopes, A., Schiavon, R. P., Sobeck, J. S., Stolberg, T., Stoll, R., Tembe, M., Trujillo, J. D., Uomoto, A., Vernieri, M., Walker, E., Weinberg, D. H., Young, E., Anthony-Brumfield, B., Bizyaev, D., Breslauer, B., Lee, N. De, Downey, J., Halverson, S., Huehnerhoff, J., Klaene, M., Leon, E., Long, D., Mahadevan, S., Malanushenko, E., Nguyen, D. C., Owen, R., Sánchez-Gallego, J. R., Sayres, C., Shane, N., Shectman, S. A., Shetrone, M., Skinner, D., Stauffer, F., Zhao, B.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.123
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.007

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 head0.011
GPT teacher head0.240
Teacher spread0.228 · 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 designBench or experimental
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

Citations310
Published2019
Admission routes1
Has abstractyes

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