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Record W1984616914 · doi:10.1002/pssa.200590012

Preface: phys. stat. sol. (a) 202/7

2005· article· en· W1984616914 on OpenAlexaboutno aff
Fred H. Pollak, J. Misiewicz, P. Sitarek

Bibliographic record

Venuephysica status solidi (a) · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor materials and interfaces
Canadian institutionsnot available
Fundersnot available
KeywordsSpectroscopySemiconductorEngineering physicsOptoelectronicsModulation (music)Materials scienceTelecommunicationsLibrary sciencePhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract We have recently observed a growing interest in using the powerful technique of optical modulation spectroscopy. These applications are related mostly to the characterization of low dimensional semiconductor structures and devices based on them. The International Workshop on Modulation Spectroscopy of Semiconductor Structures (MS 3 ) at the beginning of July 2004 gathered in Wrocław (in the southwest part of Poland) almost 40 participants, half of them from abroad. The 8 invited and 16 contributed talks were presented by the leaders of research teams from the USA, Japan, Taiwan, Canada, Germany, France, the Netherlands, Sweden, Ireland, Russia, Lithuania and Poland. Part of the MS 3 workshop was held at the Laboratory of Advanced Optical Spectroscopy, Institute of Physics, Wrocław University of Technology, where discussions on technical matter of the modulation spectroscopy were carried out in a relaxing atmosphere over a cup of coffee. The topics of the MS 3 workshop included: advantages of photoreflectance, electroreflectance, contactless electroreflectance, thermoreflectance, differential reflectance and wavelength‐modulated surface photovoltage spectroscopy. The applications of the above methods to investigate transistor, diode and laser structures including VCSELs, low dimensional structures of both wings of the spectrum, i.e. wide band gap materials like GaN, AlGaN, ZnO and low band gap materials such as GaInN(Sb)As, InAs, InSb, and FeSi 2 were demonstrated. It is our great pleasure to publish the most interesting of the MS 3 workshop presentations in this issue of physica status solidi (a). The organizers acknowledge Wrocław University of Technology, the Center of Exellence CEPHONA from the Institute of Electron Technology in Warsaw and the Polish Committee for Scientific Research for financial support of the workshop.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

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
Published2005
Admission routes1
Has abstractyes

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