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Record W2560738098 · doi:10.3847/1538-4365/228/2/12

Astrochemical Properties of Planck Cold Clumps

2017· article· en· W2560738098 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
FundersScience and Technology Facilities CouncilNational Astronomical Observatory of JapanKorea Astronomy and Space Science InstituteChinese Academy of SciencesNational Research Foundation of KoreaAcademia SinicaNational Research Foundation
KeywordsPlanckJames Clerk Maxwell TelescopeCore (optical fiber)TelescopeMolecular cloudChemical evolutionMean kinetic temperature

Abstract

fetched live from OpenAlex

Abstract We observed 13 Planck cold clumps with the James Clerk Maxwell Telescope/SCUBA-2 and with the Nobeyama 45 m radio telescope. The N 2 H + distribution obtained with the Nobeyama telescope is quite similar to SCUBA-2 dust distribution. The 82 GHz HC 3 N, 82 GHz CCS, and 94 GHz CCS emission are often distributed differently with respect to the N 2 H + emission. The CCS emission, which is known to be abundant in starless molecular cloud cores, is often very clumpy in the observed targets. We made deep single-pointing observations in DNC, HN 13 C, N 2 D + , and cyclic-C 3 H 2 toward nine clumps. The detection rate of N 2 D + is 50%. Furthermore, we observed the NH 3 emission toward 15 Planck cold clumps to estimate the kinetic temperature, and confirmed that most targets are cold (≲20 K). In two of the starless clumps we observed, the CCS emission is distributed as it surrounds the N 2 H + core (chemically evolved gas), which resembles the case of L1544, a prestellar core showing collapse. In addition, we detected both DNC and N 2 D + . These two clumps are most likely on the verge of star formation. We introduce the chemical evolution factor (CEF) for starless cores to describe the chemical evolutionary stage, and analyze the observed Planck cold clumps.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.243
Teacher spread0.226 · 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.

Study designBench or experimental
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

Citations45
Published2017
Admission routes1
Has abstractyes

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