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Record W3100741372

[no title]

2019· article· en· W3100741372 on OpenAlexfundno aff

Bibliographic record

VenueAmericanae (AECID Library) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryPlanetary Science DivisionSmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieMax-Planck-Institut für AstrophysikEötvös Loránd TudományegyetemNational Central UniversityMinistério da Ciência, Tecnologia e InovaçãoQueen's UniversityGordon and Betty Moore FoundationQueen's University BelfastUniversity of OxfordDurham UniversityYork UniversityUniversidad Nacional Autónoma de MéxicoSpace Telescope Science InstituteLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityLos Alamos National LaboratoryUniversity of WashingtonEuropean Space AgencyAlfred P. Sloan FoundationJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahOhio State UniversityU.S. Department of EnergySmithsonian InstitutionNational Aeronautics and Space AdministrationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityScience Mission DirectorateYale UniversityNational Science Foundation
KeywordsSkyComputer sciencePipeline (software)Data setData visualizationVisualizationRaw dataAstronomyComputer graphics (images)PhysicsData miningArtificial intelligenceOperating system
DOInot available

Abstract

fetched live from OpenAlex

Author: Aguado, D. S. et al.; Genre: Journal Article; Published online: 2019-01-31; Title: The fifteenth data release of the Sloan Digital Sky Surveys: First release of MaNGA-derived quantities, data visualization tools, and stellar library

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.557
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4430.389

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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations316
Published2019
Admission routes1
Has abstractyes

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