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Record W2108345010 · doi:10.1017/s0022377801001295

A note on the compression ratio in MHD shocks

2001· article· en· W2108345010 on OpenAlexaff
К. Кабин

Bibliographic record

VenueJournal of Plasma Physics · 2001
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysicsCompression ratioShock (circulatory)Compression (physics)MagnetohydrodynamicsMechanicsFlow (mathematics)Bow shock (aerodynamics)Heat capacity ratioPlasmaShock waveThermodynamicsNuclear physics

Abstract

fetched live from OpenAlex

Abstract. We present an analysis of the compression ratio in MHD shocks. Although the equation describing the compression ratio has been in the literature for decades, we believe that our results are interesting and complementary to the earlier research. We concentrate on the behavior of the compression ratio in a bow shock as a function of the angle between the shock normal and the plasma velocity. For this problem, we find non-unique solutions in certain regimes, which we investigate in detail. We also find regimes where the compression ratio in fast bow shocks achieves a local maximum in more than one location. In the last section, we consider the compression ratio in slow shocks and make some conclusions about the shape of the shock in this flow regime.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.295
Teacher spread0.261 · 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 designTheoretical or conceptual
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

Citations20
Published2001
Admission routes1
Has abstractyes

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