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Record W2010949702 · doi:10.1142/s0218625x02002737

TEMPERATURE EVOLUTION OF THE PHOTOEMISSION SPECTRA FOR THE Si(111) SURFACE USING THE LASER ANNEALING METHOD

2002· article· en· W2010949702 on OpenAlexfundno aff
Yuichi Haruyama, Shinji Matsui, Taichi Okuda, Ayumi Harasawa, T. Kinoshita, Shinichiro Tanaka, HIDEO MAKINO, Katsuo Wada

Bibliographic record

VenueSurface Review and Letters · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceHigh Energy Accelerator Research OrganizationMcGill University
KeywordsAngle-resolved photoemission spectroscopyPhotoemission spectroscopySpectral lineInverse photoemission spectroscopyAnnealing (glass)Atmospheric temperature rangeMaterials scienceX-ray photoelectron spectroscopyBinding energyLaserAtomic physicsElectronic structureAnalytical Chemistry (journal)ChemistryMolecular physicsOpticsNuclear magnetic resonanceComputational chemistry

Abstract

fetched live from OpenAlex

We have studied the electronic structures in a wide temperature range for the Si(111) surface using photoemission spectroscopy combined with the laser annealing method. The temperature dependence of the Si 2p surface-sensitive core level photoemission spectra shows some gradual changes along with the thermal broadening above ~1063 K. In addition, the spectral change in the valence band photoemission spectra was also observed across the 7 × 7–1 × 1 transition temperature. These results indicate that the surface band structure is changed along with structural change at the 7 × 7–1 × 1 transition temperature. With increase of the temperature, the shift of the Si 2p core-level photoemission spectra to the lower binding energy side was observed. We discuss the temperature-induced effects such as the thermal broadening and the observed shift.

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 score0.004

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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