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Record W2952155064 · doi:10.3390/app9122531

A Low-Cost Terahertz Camera

2019· article· en· W2952155064 on OpenAlexafffund
F. Blanchard, J. E. Nkeck, Dominique Matte, Riad Nechache, David G. Cooke

Bibliographic record

VenueApplied Sciences · 2019
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsMcGill UniversityÉcole de Technologie Supérieure
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsTerahertz radiationComputer scienceDigital cameraOpticsMaterials scienceOptoelectronicsElectronic engineeringArtificial intelligencePhysicsEngineering

Abstract

fetched live from OpenAlex

Cost effective imaging is required for a wide range of scientific and engineering applications. For electromagnetic waves in the terahertz (THz) frequency range, a key missing element that has prevented widespread applications in this spectral range is an inexpensive and efficient imaging device. In recent years, vanadium oxide based thermal sensors have rapidly entered the market for night vision capability. At the same time, sensors based on this technology have been applied to the THz domain, but with two orders of magnitude larger pricing range. Here we show that, with a simple modification, a commercially available thermal imaging camera can function as a THz imaging device. By comparing a commercially available THz camera and this low-cost device, we identify the main sensitivity difference is not attributed to anything intrinsic to the devices, but rather to the analog-to-digital converter and dynamic background subtraction capability. This demonstration of a low-cost THz camera may aid in the rapid development of affordable THz imaging solutions for industrial and scientific applications.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations11
Published2019
Admission routes2
Has abstractyes

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