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Properties of flat-spectrum radio-loud narrow-line Seyfert 1 galaxies

2015· article· en· W3101036847 on OpenAlexafffund
L. Foschini, M. Berton, A. Caccianiga, S. Ciroi, V. Cracco, B. M. Peterson, E. Angelakis, V. Braito, L. Fuhrmann, Luigi Gallo

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsSaint Mary's University
FundersLawrence Berkeley National LaboratoryBrookhaven National LaboratoryAstrophysics Science DivisionSmithsonian Astrophysical ObservatoryRussian Foundation for Basic ResearchAstrophysics DivisionYork UniversityDynasty FoundationCarnegie Mellon UniversityOffice of ScienceUniversity of WashingtonPrinceton UniversityAlfred P. Sloan FoundationJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityGoddard Space Flight CenterHarvard UniversityOhio State UniversitySmithsonian InstitutionU.S. Department of EnergyCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationJet Propulsion LaboratoryNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityYale UniversityNational Science Foundation
KeywordsPhysicsAstrophysicsQuasarBlazarActive galactic nucleusGalaxyAstronomyAccretion (finance)Radio galaxySpectral lineBlack hole (networking)Jet (fluid)Eddington luminosityFlux (metallurgy)Gamma ray

Abstract

fetched live from OpenAlex

Author: Foschini, L. et al.; Genre: Journal Article; Issued: 2015-03; Keywords: galaxies: Seyfert, galaxies: jets, quasars: general, BL Lacertae objects: general; Title: Properties of flat-spectrum radio-loud narrow-line Seyfert 1 galaxies

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.215
Teacher spread0.197 · 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

Citations167
Published2015
Admission routes2
Has abstractyes

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