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The Macquarie/AAO/Strasbourg H  Planetary Nebula Catalogue: MASH

2006· article· en· W2154880253 on OpenAlexaff
Q. A. Parker, A. Acker, D. J. Frew, M. Hartley, A. E. J. Peyaud, F. Ochsenbein, S. Phillipps, D. Russeil, S. F. Beaulieu, Martin Cohen, J. Köppen, B. Miszalski, D. H. Morgan, R. A. H. Morris, Michael Pierce, A. E. Vaughan

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPlanetary nebulaPhysicsGalactic planeBulgeAstrophysicsSurface brightnessAstronomyNebulaGalactic CenterLuminosityStarsGalaxy

Abstract

fetched live from OpenAlex

We present the Macquarie/AAO/Strasbourg Hα Planetary Nebula Catalogue (MASH) of over 900 true, likely and possible new Galactic planetary nebulae (PNe) discovered from the AAO/UKST Hα survey of the southern Galactic plane. The combination of depth, resolution, uniformity and areal coverage of the Hα survey has opened up a hitherto unexplored region of parameter space permitting the detection of this significant new PN sample. Away from the Galactic bulge the new PNe are typically more evolved, of larger angular extent, of lower surface brightness and more obscured (i.e. extinguished) than those in most previous surveys. We have also doubled the number of PNe in the Galactic bulge itself and although most are compact, we have also found more evolved examples. The MASH catalogue represents the culmination of a seven-year programme of identification and confirmatory spectroscopy. A key strength is that the entire sample has been derived from the same, uniform observational data. The 60 per cent increase in known Galactic PNe represents the largest ever incremental sample of such discoveries and will have a significant impact on many aspects of PN research. This is especially important for studies at the faint end of the PN luminosity function which was previously poorly represented.

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 score0.139
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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

Citations273
Published2006
Admission routes1
Has abstractyes

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