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Record W4323844864 · doi:10.21203/rs.3.rs-2662654/v1

Polarimetric study of the solar corona during the total solar eclipse on July 02, 2019 with a liquid crystal polarimeter

2023· preprint· en· W4323844864 on OpenAlexaboutno aff
Alessandro Liberatore, Joe Zender, Gerardo Capobianco, Silvano Fineschi, O. Panasenco, Dana Tomuta, Manuel Castillo, Miguel Pérez-Ayúcar

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
FundersCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsSolar eclipsePolarimeterPolarimetryOrbiterCoronagraphOpticsEclipseRemote sensingPhysicsCoronal mass ejectionAstronomyMaterials scienceMeteorologyExoplanetSolar windGeographyPlasmaStars

Abstract

fetched live from OpenAlex

Abstract The results obtained during the total Solar Eclipse on July 2, 2019, in Chile are presented together with the Eclipse K-corona Polarimeter (EKPol). The EKPol is equipped with an electro-optically modulating Liquid Crystal Variable Retarder (LCVR) for the polarimetric observation of the solar corona. The use of this technology has been an important ground-based test for the application of this technology in space-based observatories. The usage of LCVRs in a polarization rotator configuration, allows the replacement of mechanically rotating retarders avoiding moving parts and reducing noise, failure probability, and mass. Indeed, EKPol was developed as a technology demonstrator for the Metis coronagraph on-board Solar Orbiter. The results, from the composition of the image to the electron density map evaluation, are compared and are consistent with what is obtained by other ground-based and space-based instruments, and with past EKPol campaigns.

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 score0.019
Threshold uncertainty score0.038

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 communication0.0010.000
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 head0.033
GPT teacher head0.324
Teacher spread0.292 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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