MétaCan
Menu
Back to cohort
Record W3204032529 · doi:10.1103/physrevb.108.045106

Looking beyond the surface with angle-resolved photoemission spectroscopy

2023· article· en· W3204032529 on OpenAlexafffund
Ryan Day, Ilya Elfimov, A. Damascelli

Bibliographic record

VenuePhysical review. B./Physical review. B · 2023
Typearticle
Languageen
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsUniversity of British Columbia
FundersCanada First Research Excellence FundCanada Excellence Research Chairs, Government of CanadaCanada Foundation for InnovationBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsInverse photoemission spectroscopyContext (archaeology)Photoemission spectroscopyAngle-resolved photoemission spectroscopySensitivity (control systems)Materials scienceSurface (topology)SpectroscopyInterpretation (philosophy)Electronic structureX-ray photoelectron spectroscopyEnergy (signal processing)Connection (principal bundle)SlabAtomic physicsCondensed matter physicsPhysicsNuclear magnetic resonanceQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

The issue of surface sensitivity and its relationship with the interpretation of spectral features observed in angle-resolved photoemission spectroscopy experiments is investigated. Rather than attempt to make an explicit connection to bulk electronic structure calculations, we take the approach of exploring this issue within the natural context of a vacuum-terminated crystalline slab. Doing so, we reconcile the empirical reality of reliable ${k}_{z}$ fidelity with acute surface sensitivity of this technique. In addition, we identify several critical issues which impact the estimation of ${k}_{F}$, band velocity, and self-energy from photoemission experiments.

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)0.003
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.332
Teacher spread0.316 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePhysical review. B./Physical review. BSame topicElectronic and Structural Properties of OxidesFrench-language works237,207