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Record W4292484707 · doi:10.3389/fspas.2022.940027

Three-dimensional magnetic fields of molecular clouds

2022· article· en· W4292484707 on OpenAlexafffund
Mehrnoosh Tahani

Bibliographic record

VenueFrontiers in Astronomy and Space Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsNational Research Council CanadaDominion Astrophysical ObservatoryHerzberg Institute of Astrophysics
FundersNational Research Council Canada
KeywordsPhysicsMagnetic fieldMolecular cloudStarsAstrophysicsGalactic planeInterstellar mediumLine-of-sightSkyAstronomyGalaxy

Abstract

fetched live from OpenAlex

To investigate the role of magnetic fields in the evolution of the interstellar medium, formation and evolution of molecular clouds, and ultimately the formation of stars, their three-dimensional (3D) magnetic fields must be probed. Observing only one component of magnetic fields (along the line of sight or parallel to the plane of the sky) is insufficient to identify these 3D vectors. In recent years, novel techniques for probing each of these two components and integrating them with additional data (from observations or models), such as Galactic magnetic fields or magnetic field inclination angles, have been developed, in order to infer 3D magnetic fields. We review and discuss these advancements, their applications, and their future direction.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.317

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 integrity0.0000.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 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

Citations11
Published2022
Admission routes2
Has abstractyes

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