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Record W2146896318 · doi:10.1088/0004-637x/710/2/1247

THE MASS DISTRIBUTION OF STARLESS AND PROTOSTELLAR CORES IN GOULD BELT CLOUDS

2010· article· en· W2146896318 on OpenAlexaff
Sarah Sadavoy, James Di Francesco, Sylvain Bontemps, S. T. Megeath, L. M. Rebull, Erin Allgaier, S. Carey, Robert Gutermuth, Tracy L. Huard, Caer‐Eve McCabe, James Muzerolle, A. Noriega‐Crespo, Deborah Padgett, S. Terebey

Bibliographic record

VenueThe Astrophysical Journal · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsNational Research Council CanadaUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsOphiuchusAstrophysicsPhysicsJames Clerk Maxwell TelescopeMolecular cloudSerpensPhotometry (optics)AstronomyStar formationYoung stellar objectProtostarGalaxyStars

Abstract

fetched live from OpenAlex

Using data from the SCUBA Legacy Catalogue (850 um) and Spitzer Space Telescope (3.6 - 70 um), we explore dense cores in the Ophiuchus, Taurus, Perseus, Serpens, and Orion molecular clouds. We develop a new method to discriminate submillimeter cores found by SCUBA as starless or protostellar, using point source photometry from Spitzer wide field surveys. First, we identify infrared sources with red colors associated with embedded young stellar objects (YSOs). Second, we compare the positions of these YSO-candidates to our submillimeter cores. With these identifications, we construct new, self-consistent starless and protostellar core mass functions (CMFs) for the five clouds. We find best fit slopes to the high-mass end of the CMFs of -1.26 +/- 0.20, -1.22 +/- 0.06, -0.95 +/- 0.20, and -1.67 +/- 0.72 for Ophiuchus, Taurus, Perseus, and Orion, respectively. Broadly, these slopes are each consistent with the -1.35 power-law slope of the Salpeter IMF at higher masses, but suggest some differences. We examine a variety of trends between these CMF shapes and their parent cloud properties, potentially finding a correlation between the high-mass slope and core temperature. We also find a trend between core mass and effective size, but we are very limited by sensitivity. We make similar comparisons between core mass and size with visual extinction (for A_V >= 3) and find no obvious trends. We also predict the numbers and mass distributions of cores that future surveys with SCUBA-2 may detect in each of these clouds.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.343

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 integrity0.0000.001
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 head0.235
Teacher spread0.228 · 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 designTheoretical or conceptual
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

Citations111
Published2010
Admission routes1
Has abstractyes

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