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Record W4288086072 · doi:10.1051/0004-6361/201936280

Could bow-shaped magnetic morphologies surround filamentary molecular clouds? The 3D magnetic field structure of Orion-A

2019· article· en· W4288086072 on OpenAlexaff
Mehrnoosh Tahani, R. Plume, J. C. Brown, J. D. Soler, J. Kainulainen

Bibliographic record

VenueChalmers Research (Chalmers University of Technology) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of CalgaryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsMorphology (biology)Monte Carlo methodMagnetic fieldPhysicsFaraday effectToroidAstrophysicsGeologyStatistics

Abstract

fetched live from OpenAlex

Context. A new method based on Faraday rotation measurements recently found the line-of-sight component of magnetic fields in Orion-A and showed that their direction changes from the eastern side of this filamentary structure to its western side. Three possible magnetic field morphologies that can explain this reversal across the Orion-A region are toroidal, helical, and bow-shaped morphologies. Aims. In this paper, we constructed simple models to represent these three morphologies and compared them with the available observational data to find the most probable morphology(ies). Methods. We compared the observations with the models and used probability values and a Monte Carlo analysis to determine the most likely magnetic field morphology among these three morphologies. Results. We found that the bow morphology had the highest probability values, and that our Monte-Carlo analysis suggested that the bow morphology was more likely. Conclusions. We suggest that the bow morphology is the most likely and the most natural of the three morphologies that could explain a magnetic field reversal across the Orion-A filamentary structure (i.e., bow, helical and toroidal morphologies).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.255
Teacher spread0.242 · 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 designQualitative
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

Citations46
Published2019
Admission routes1
Has abstractyes

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