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Record W2294173525 · doi:10.1103/physrevb.70.014517

Optical conductivity in nonequilibrium<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>d</mml:mi></mml:mrow></mml:math>-wave superconductors

2004· article· lv· W2294173525 on OpenAlexaff
J. P. Ćarbotte, E. Schachinger

Bibliographic record

VenuePhysical Review B · 2004
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsMcMaster University
Fundersnot available
KeywordsQuasiparticleNon-equilibrium thermodynamicsThermal conductivitySuperconductivityDistribution (mathematics)Condensed matter physicsPhysicsThermodynamicsMaterials scienceAnalytical Chemistry (journal)ChemistryMathematicsMathematical analysisChromatography

Abstract

fetched live from OpenAlex

We consider the optical conductivity of a $d$-wave BCS superconductor in the presence of a nonequilibrium distribution of excess quasiparticles. Two different simplified models used in the past for the $s$-wave case are considered and results compared. In the ${T\phantom{\rule{0.1em}{0ex}}}^{*}$ model of Parker the excess quasiparticles are assumed to be in a thermal distribution at some temperature ${T\phantom{\rule{0.1em}{0ex}}}^{*}$ larger than the equilibrium sample temperature. In the ${\ensuremath{\mu}}^{*}$ model of Owen and Scalapino a chemical potential is introduced to accommodate the excess quasiparticles. Some of the results obtained are specific to the model; most are qualitatively similar in both.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.266
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 designSimulation or modeling
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

Citations7
Published2004
Admission routes1
Has abstractyes

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