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Water in star-forming regions with

2013· article· en· W6884489859 on OpenAlexfundno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMinisterio de Ciencia e InnovaciónNederlandse Organisatie voor Wetenschappelijk OnderzoekL'Oreal USANational Aeronautics and Space Administration
KeywordsProtostarSpectral lineContext (archaeology)Line (geometry)Accretion (finance)Dissipation

Abstract

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Context. Understanding the physical phenomena involved in the earlierst stages of protostellar evolution requires knowledge of the heating and cooling processes that occur in the surroundings of a young stellar object. Spatially resolved information from its constituent gas and dust provides the necessary constraints to distinguish between different theories of accretion energy dissipation into the envelope. Aims. Our aims are to quantify the far-infrared line emission from low-mass protostars and the contribution of different atomic and molecular species to the gas cooling budget, to determine the spatial extent of the emission, and to investigate the underlying excitation conditions. Analysis of the line cooling will help us characterize the evolution of the relevant physical processes as the protostar ages. Methods. Far-infrared Herschel-PACS spectra of 18 low-mass protostars of various luminosities and evolutionary stages are studied in the context of the WISH key program. For most targets, the spectra include many wavelength intervals selected to cover specific CO, H2O, OH, and atomic lines. For four targets the spectra span the entire 55–200 μm region. The PACS field-of-view covers ~47″ with the resolution of 9.4″. Results. Most of the protostars in our sample show strong atomic and molecular far-infrared emission. Water is detected in 17 out of 18 objects (except TMC1A), including 5 Class I sources. The high-excitation H2O 818–707 63.3 μm line (Eu/kB = 1071 K) is detected in 7 sources. CO transitions from J = 14−13 up to J = 49 − 48 are found and show two distinct temperature components on Boltzmann diagrams with rotational temperatures of ~350 K and ~700 K. H2O has typical excitation temperatures of ~150 K. Emission from both Class 0 and I sources is usually spatially extended along the outflow direction but with a pattern that depends on the species and the transition. In the extended sources, emission is stronger off source and extended on ≥10 000 AU scales; in the compact sample, more than half of the flux originates within 1000 AU of the protostar. The H2O line fluxes correlate strongly with those of the high-J CO lines, both for the full array and for the central position, as well as with the bolometric luminosity and envelope mass. They correlate less strongly with OH fluxes and not with [O i] fluxes. In contrast, [O i] and OH often peak together at the central position. Conclusions. The PACS data probe at least two physical components. The H2O and CO emission very likely arises in non-dissociative (irradiated) shocks along the outflow walls with a range of pre-shock densities. Some OH is also associated with this component, most likely resulting from H2O photodissociation. UV-heated gas contributes only a minor fraction to the CO emission observed by PACS, based on the strong correlation between the shock-dominated CO 24–23 line and the CO 14–13 line. [O i] and some of the OH emission probe dissociative shocks in the inner envelope. The total far-infrared cooling is dominated by H2O and CO, with the fraction contributed by [O i] increasing for Class I sources. Consistent with previous studies, the ratio of total far-infrared line emission over bolometric luminosity decreases with the evolutionary state.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.213
Teacher spread0.203 · 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.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2013
Admission routes1
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