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Record W4415482608 · doi:10.1109/lpt.2025.3624657

Terahertz Polarization-Resolved Single Pixel Imaging of Wood Materials With Complex Defects

2025· article· W4415482608 on OpenAlexafffund
Seth N. Lowry, M. Reid, Christopher M. Collier

Bibliographic record

VenueIEEE Photonics Technology Letters · 2025
Typearticle
Language
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Northern British ColumbiaUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTerahertz radiationPixelTerahertz metamaterialsTerahertz spectroscopy and technologyFar-infrared laserQuality (philosophy)Photomixing

Abstract

fetched live from OpenAlex

Terahertz imaging is a promising modality for non-destructive evaluation and quality control of wood building materials, particularly given the polarization-specific responses of wood. Single pixel imaging allows efficient, low-cost configurations—crucial for evolving terahertz systems approaching adoption in industry. In this work, a polarization-resolved terahertz single pixel imaging system, with a source frequency of 0.29 THz, is used to identify complex defects in wood materials. The recovered polarization-resolved terahertz images successfully locate and map the structure of wood knots 3 mm in diameter, concealed shallow cuts 1 mm deep, and growth ring structures throughout the material. This work demonstrates an effective application of polarization-resolved terahertz single pixel imaging for non-destructive wood product inspection.

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)
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 score0.093
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.217
Teacher spread0.210 · 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 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

Citations2
Published2025
Admission routes2
Has abstractyes

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