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Record W2003368276 · doi:10.1086/425552

Cosmic Star Formation History to<i>z</i> = 1 from a Narrow Emission Line-selected Tunable-Filter Survey

2004· article· en· W2003368276 on OpenAlexaff
Karl Glazebrook, Jeffrey Tober, Scott L. Thomson, Joss Bland‐Hawthorn, Roberto Abraham

Bibliographic record

VenueThe Astronomical Journal · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhysicsAstrophysicsStar formationRedshiftGalaxyLuminosityJames Clerk Maxwell TelescopeAstronomyHubble Deep FieldEmission spectrumLine (geometry)PopulationSpectral lineDemography

Abstract

fetched live from OpenAlex

We report the results of a deep 3D imaging survey of the Hubble Deep Field North using the Taurus Tunable Filter and the William Herschel Telescope. This survey was designed to search for new line emitting populations of objects missed by other techniques and to measure the cosmic star-formation rate density from a line-selected survey. We observed in three contiguous sequences of narrow band slices in the 7100, 8100 and 9100A regions of the spectrum, corresponding to a cosmological volume of up to 1000 Mpc^3 at z=1, down to a flux limit of 2x 10^-17 ergs cm^-2 s^-1. The survey is deep enough to be highly complete for low line luminosity galaxies. Cross-matching with existing spectroscopy in the field results in a small line-luminosity limited sample, with very highly redshift identification completeness containing seven [OII], Hbeta and Halpha emitters over the redshift range 0.3 - 0.9. Treating this as a direct star-formation rate selected sample we estimate the star-formation history of the Universe to z=1. We find no evidence for any new population of line emitting objects contributing significantly to the cosmological star-formation rate density. Rather from our complete narrow-band sample we find the star-formation history is consistent with earlier estimates from broad-band imaging surveys and other less deep line-selected surveys.

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)0.001
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 score0.040
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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

Citations33
Published2004
Admission routes1
Has abstractyes

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