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Record W2043253832 · doi:10.1063/1.4896175

New experimental platform to study high density laser-compressed matter

2014· article· en· W2043253832 on OpenAlexaff
M. Gauthier, L. B. Fletcher, A. Ravasio, Eric Galtier, E. J. Gamboa, E. Granados, J. B. Hastings, Philip Heimann, H. J. Lee, Bob Nagler, Andreas Schropp, A. E. Gleason, T. Döppner, S. Le Pape, T. Ma, A. Pak, M. J. MacDonald, S. J. Ali, B. Barbrel, R. W. Falcone, D. Kraus, Zhijiang Chen, MZ Mo, M. S. Wei, S. H. Glenzer

Bibliographic record

VenueReview of Scientific Instruments · 2014
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of Alberta
FundersLawrence Livermore National LaboratoryBasic Energy SciencesMinisterio de Economía y CompetitividadOffice of ScienceVolkswagen FoundationU.S. Department of Energy
KeywordsLaserMaterials scienceOpticsPhysics

Abstract

fetched live from OpenAlex

We have developed a new experimental platform at the Linac Coherent Light Source (LCLS) which combines simultaneous angularly and spectrally resolved x-ray scattering measurements. This technique offers a new insights on the structural and thermodynamic properties of warm dense matter. The < 50 fs temporal duration of the x-ray pulse provides near instantaneous snapshots of the dynamics of the compression. We present a proof of principle experiment for this platform to characterize a shock-compressed plastic foil. We observe the disappearance of the plastic semi-crystal structure and the formation of a compressed liquid ion-ion correlation peak. The plasma parameters of shock-compressed plastic can be measured as well, but requires an averaging over a few tens of shots.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 designBench or experimental
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

Citations14
Published2014
Admission routes1
Has abstractyes

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