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Record W4386361074 · doi:10.3847/25c2cfeb.c2b0c4e5

Enabling Discoveries in Heliospheric Science through Laboratory Plasma Experiments

2023· article· en· W4386361074 on OpenAlexaff
Emily Lichko, Douglass Endrizzi, James Juno, Joseph Olson, S. Dorfman, Rachel Young, Saikat Chakraborty Thakur, Evdokiya Kostadinova, Mel Abler, Feiyu Li, D. B. Schaeffer, K. G. Klein, Rachael Filwett, Yeimy J. Rivera, Silvina Guidoni, Arian Timm, P. V. Heuer, Jason TenBarge, Lorin Matthews, Lev Arzamasskiy, T. F. Du, G. G. Howes, Luca Comisso, F. Effenberg, Dan Fries, Jonathan Squire, Peiyun Shi, Alfred Mallet, J. L. Verniero, L. Ofman, Romain Meyrand, Kimberly Moreland, Liang Wang, Subash Adhikari, Vincent Ledvina, Chuanfei Dong, Chris R. Gilly, Hossein Ghadjari, Christopher Light, Ranadeep Sarkar, Yi‐Hsin Liu, M. Swisdak, B. J. Lynch, Anwesha Maharana, Xiangrong Fu, J. A. Wanliss, Pankaj Kumar, P. A. Cassak, Anshu Kumari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversity of Calgary
FundersAuburn UniversityUniversity of Wisconsin-Madison
KeywordsPlasmaPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Whitepaper #236 in the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033. Main topics: basic research; infrastructure/workforce/other programmatic. Additional topics: fundamental space plasma theory; state of the profession; laboratory space plasma […]

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 score0.634
Threshold uncertainty score0.370

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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
Published2023
Admission routes1
Has abstractyes

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