MétaCan
Menu
Back to cohort
Record W2025036673 · doi:10.1126/science.aaa4990

Quasiparticle mass enhancement approaching optimal doping in a high- <i>T</i> <sub>c</sub> superconductor

2015· article· en· W2025036673 on OpenAlexafffund
B. J. Ramshaw, Suchitra E. Sebastian, R. McDonald, James Day, B. S. Tan, Zengwei Zhu, Jon Betts, Ruixing Liang, D. A. Bonn, W. N. Hardy, N. Harrison

Bibliographic record

VenueScience · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British Columbia
FundersHigh Magnetic Field Laboratory, Chinese Academy of SciencesH2020 European Research CouncilDivision of Materials ResearchNatural Sciences and Engineering Research Council of CanadaEuropean CommissionRoyal SocietyCanadian Institute for Advanced ResearchNational High Magnetic Field LaboratorySeventh Framework ProgrammeU.S. Department of EnergyNational Science Foundation
KeywordsCondensed matter physicsQuasiparticlePhysicsPseudogapQuantum critical pointSuperconductivityCuprateEffective mass (spring–mass system)Quantum phase transitionCritical point (mathematics)Quantum mechanicsPhase transition

Abstract

fetched live from OpenAlex

In the quest for superconductors with higher transition temperatures (T(c)), one emerging motif is that electronic interactions favorable for superconductivity can be enhanced by fluctuations of a broken-symmetry phase. Recent experiments have suggested the existence of the requisite broken-symmetry phase in the high-T(c) cuprates, but the impact of such a phase on the ground-state electronic interactions has remained unclear. We used magnetic fields exceeding 90 tesla to access the underlying metallic state of the cuprate YBa2Cu3O(6+δ) over a wide range of doping, and observed magnetic quantum oscillations that reveal a strong enhancement of the quasiparticle effective mass toward optimal doping. This mass enhancement results from increasing electronic interactions approaching optimal doping, and suggests a quantum critical point at a hole doping of p(crit) ≈ 0.18.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.250
Teacher spread0.222 · 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

Citations209
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueScienceSame topicPhysics of Superconductivity and MagnetismFrench-language works237,207