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Record W2283777332 · doi:10.1002/asna.201512280

The infrared properties of the GPS and CSS radio sources

2016· article· en· W2283777332 on OpenAlexaff
C. P. O’Dea

Bibliographic record

VenueAstronomische Nachrichten · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPhysicsGlobal Positioning SystemAstrophysicsStar formationStarsGalaxyAstronomyTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Abstract I review the results of three Spitzer studies of GHz‐Peaked Spectrum (GPS) and Compact Steep Spectrum (CSS) radio galaxies. The luminosity of the IR continuum and the high ionization lines confirm that some GPS/CSS can have central engines which are similar to those of the extended powerful radio sources. This is consistent with the hypothesis that some GPS/CSS can evolve to become the large‐scale sources. Warm H2 is common in the GPS/CSS sources consistent with feedback via jet‐ISM interaction. The GPS/CSS seem to have higher star formation rates than typical (2JY + 3CRR) radio sources. This should be confirmed with a larger sample. If compact sources interact with dense, clumpy star forming clouds and if the interaction with the dense medium sufficiently enhances the radio power, these star forming galaxies with enhanced radio emission will be selected for the current bright samples of GPS and CSS sources. This will increase the number of GPS and CSS sources which are observed to be forming stars. If radio sources have longer lives and/or star formation is more common in large radio galaxies, the need for a new population of star forming compact sources with enhanced radio emission is reduced. (© 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

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

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 head0.174
Teacher spread0.167 · 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 teacher head, 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

Citations5
Published2016
Admission routes1
Has abstractyes

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