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Record W2170682429 · doi:10.1364/ao.48.006541

Simultaneous composition and thickness measurement of paper using terahertz time-domain spectroscopy

2009· article· en· W2170682429 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Optics · 2009
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsHoneywell (Canada)Simon Fraser University
Fundersnot available
KeywordsMonte Carlo methodOpticsSpectroscopyMaterials scienceTerahertz radiationTerahertz spectroscopy and technologyTime domainTransmission (telecommunications)Terahertz time-domain spectroscopyPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

We present a noncontact method for quantitative composition and thickness monitoring of flat sheet products using terahertz time-domain spectroscopy. We apply the method to obtain simultaneous measurement of thickness and moisture content of paper sheets. The paper is modeled as an effective medium of water mixed with fibers, and model parameters are estimated from fits to the measured transmission amplitude. We demonstrate the method on two different paper samples and obtain uncertainties that are comparable with existing sensor technology. Monte Carlo simulations indicate that these uncertainties can be reduced further by at least an order of magnitude.

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.

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 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 score0.197
Threshold uncertainty score0.468

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)0.0000.000

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 head0.007
GPT teacher head0.210
Teacher spread0.202 · 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