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Record W2025277467 · doi:10.1017/s1743921313008156

A First Look at the Disk Population in the Auriga-California Molecular Cloud

2013· article· en· W2025277467 on OpenAlexaff
H. Broekhoven-Fiene, Brenda C. Matthews, P. M. Harvey

Bibliographic record

VenueProceedings of the International Astronomical Union · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsNational Research Council CanadaUniversity of Victoria
Fundersnot available
KeywordsMolecular cloudAstrophysicsCircumstellar diskCloud computingPhysicsPopulationStar formationDebris diskAstronomyPlanetPlanetary systemStarsComputer science

Abstract

fetched live from OpenAlex

Abstract The Auriga-California Molecular Cloud (AMC) is one of two nearby (within 500 pc) giant molecular clouds, the other being the Orion A Molecular Cloud (OMC). We aim to study the properties of circumstellar disks in the AMC to compare the planet formation potential and processes within the AMC to those for other clouds. A first look with measurements from Spitzer observations suggests that AMC disk properties, such as the distribution of disk luminosities and the evolution of the mid-IR excesses, are not vastly different from those in other regions. Follow-up observations in the submm, mm and cm can be used to measure disk masses and the degree of grain growth from spectral slopes to more completely characterize the disk population.

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)0.000
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 score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.005
GPT teacher head0.199
Teacher spread0.195 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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