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Record W2111193103 · doi:10.5539/mas.v5n2p25

3He-3He Scattering in 3He-HeII Mixtures at Low Temperatures

2011· article· en· W2111193103 on OpenAlexvenueno aff
B.R. Joudeh

Bibliographic record

VenueModern Applied Science · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum, superfluid, helium dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsScatteringCross section (physics)Range (aeronautics)Atomic physicsScattering lengthHelium-3Resonance (particle physics)PhysicsMaterials scienceChemistryOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The total and viscosity cross sections of 3He-3He collisions in HeII are calculated. The basic achievement of the paper is the prediction of the Ramsauer-Townsend effect in this mixture. The RT minimum appears as a result of a balance between attractive short-range and repulsive zero-range interactions. In the low- energy limit the cross sections are dominated by S-wave scattering. In this limit, these cross sections are strongly modified by many-body effects. The influence of S-scattering decreases with increasing pressure and concentration because of the overall repulsion of medium effects. The effect of the P-wave scattering appears as a resonance-like behavior (peak structure) in the total cross section. This peak structure increases with pressure and concentration. For high energies, these cross sections are independent of pressure and concentration. This indicates that the high-energy behavior is dominated by the self-energy contribution; and the medium effects can be neglected.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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