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Record W2965825737 · doi:10.1088/1538-3873/ab35f4

The Kinematic Distances of SNR G16.7+0.1 and G15.9+0.2 by Analyzing H i Absorption Spectra

2019· article· en· W2965825737 on OpenAlexaff

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsMaserSpectral lineKinematicsSupernova remnantSupernovaAbsorption (acoustics)Shock (circulatory)

Abstract

fetched live from OpenAlex

We build H i absorption spectra toward Supernova Remnant (SNRs) G16.7+0.1 and G15.9+0.2 using the THOR survey data. With the absorption spectra, we give a new distance range of 7–16 kpc for G15.9+0.2. We also resolve the near/far-side distance ambiguity of G16.7+0.1 and confirm its kinematic distance of about 14 kpc. In addition, we analyze the CO ( J = 3–2) spectra toward G16.7+0.1 and find obvious CO emission at the 20 km s −1 OH 1720 MHz maser site. This supports Reynoso & Mangum suggestions that the velocity difference between the maser and southern molecular cloud is caused by the shock acceleration. We discuss the impact of the distances on other physical parameters of the two SNRs.

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 score0.004
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)0.0010.000

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 head0.004
GPT teacher head0.194
Teacher spread0.189 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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