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Record W2595355550 · doi:10.1139/cjp-2016-0836

Atomic physics and solar polarimetry

2017· article· en· W2595355550 on OpenAlexvenueno aff
P. G. Judge

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsPhysicsSolar telescopePolarimetrySolar physicsSolar atmosphereMagnetic fieldTelescopeAstronomyAstrophysicsOptics

Abstract

fetched live from OpenAlex

Major outstanding problems in solar physics relate to solar magnetism. Spectropolarimetry offers the best, and sometimes only, method of obtaining accurate measurements of the Sun’s magnetic field. New 1.5–2 m class telescopes with adaptive optics have come on line, and the Daniel K. Inouye 4 m Solar Telescope (DKIST) will begin observing in 2019. The calibration of polarized light entering such a large and polarizing ground-based telescope represents difficult challenges. This paper explores how special polarization properties of particular atomic transitions may provide calibration data, augmenting or even avoiding time-consuming calibration observations, as well as science data. This initial study concludes that solar spectral lines exist with special polarization properties, allowing the telescope calibration to be determined. The Sun’s visible and infrared spectrum is dominated by lines of neutral atoms and singly charged ions of iron and other complex atoms. Both solar and atomic physics should jointly benefit from telescopic advances, as observers explore regimes of broader wavelength ranges, and higher spatial resolutions and polarimetric sensitivities, than they have reached in the past. Further work is in progress to identify particular transitions of practical use to aid in calibrations.

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 score0.436
Threshold uncertainty score0.780

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 communication0.0000.000
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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