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Record W2169580634 · doi:10.1109/tasc.2005.850555

Modeling and Analysis of High-Temperature Superconductor Terahertz Photomixers

2005· article· en· W2169580634 on OpenAlexaff
D. Saeedkia, R.R. Mansour, S. Safavi‐Naeini

Bibliographic record

VenueIEEE Transactions on Applied Superconductivity · 2005
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTerahertz radiationPhotocurrentMaterials sciencePhotomixingHigh-temperature superconductivitySuperconductivityOptoelectronicsPhotoconductivityCondensed matter physicsLaserOpticsFar-infrared laserPhysicsTerahertz metamaterials

Abstract

fetched live from OpenAlex

Photomixing phenomenon in superconductors is studied. For a photo-excited superconductor film the fundamental equations for the carriers motion inside the superconductor material have been used in connection with the two-temperature model to find an analytic expression for the generated terahertz (THz) photocurrent inside the film. The dependency of the resulting photocurrent on the material and laser parameters, temperature, and photomixer configuration for a photomixer made of YBa/sub 2/Cu/sub 3/O/sub 7-/spl delta// high-temperature superconductor is studied.

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)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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

Citations22
Published2005
Admission routes1
Has abstractyes

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