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Record W2070002915 · doi:10.1109/ted.2012.2231682

Measurement of UV from a Microplasma by a Microfabricated Amorphous Selenium Detector

2012· article· en· W2070002915 on OpenAlexaff
Shiva Abbaszadeh, Karim S. Karim, Vassili Karanassios

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2012
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicroplasmaDetectorOptoelectronicsResponsivityNoise (video)PhotonMaterials scienceSpectrometerParticle detectorOpticsPhotodetectorSIGNAL (programming language)Analytical Chemistry (journal)PhysicsChemistryPlasma

Abstract

fetched live from OpenAlex

We spectrally demonstrate for the first time that an amorphous selenium metal-semiconductor-metal detector can be used for the measurement of ultraviolet photons (200-400 nm) generated from a portable battery-operated microplasma that is used as a light source. An advantage of this low-cost detector is that the device structure allows photons to strike the light-sensitive layer directly rather than through electrodes or blocking layers. Another advantage is that despite operation at high electric fields of up to 43 V/μm, the dark current of the detector at room temperature is 3 pA/mm2. Therefore, detector cooling is not required, and this facilitates portability for measurements on-site (i.e., in the field and away from a laboratory). Spectral response was monitored using a scanning monochromator, and it was compared with that obtained by a portable spectrometer fitted with a linear charge-coupled device detector. To demonstrate detector responsivity, emission signals with an appreciable signal-to-noise ratio were obtained by introducing nanogram amounts of the sample into the microplasma.

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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

Citations40
Published2012
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Electron DevicesSame topicLuminescence Properties of Advanced MaterialsFrench-language works237,207