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Record W2001748200 · doi:10.1118/1.4892381

A Raman cell based on hollow core photonic crystal fiber for human breath analysis

2014· article· en· W2001748200 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Cancer Society
KeywordsRaman spectroscopyBreath gas analysisRaman scatteringMaterials sciencePhotonic-crystal fiberAnalytical Chemistry (journal)OpticsOptoelectronicsChemistryWavelengthChromatography

Abstract

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PURPOSE: Breath analysis has a potential prospect to benefit the medical field based on its perceived advantages to become a point-of-care, easy to use, and cost-effective technology. Early studies done by mass spectrometry show that volatile organic compounds from human breath can represent certain disease states of our bodies, such as lung cancer, and revealed the potential of breath analysis. But mass spectrometry is costly and has slow-turnaround time. The authors' goal is to develop a more portable and cost effective device based on Raman spectroscopy and hollow core-photonic crystal fiber (HC-PCF) for breath analysis. METHODS: Raman scattering is a photon-molecular interaction based on the kinetic modes of an analyte which offers unique fingerprint type signals that allow molecular identification. HC-PCF is a novel light guide which allows light to be confined in a hollow core and it can be filled with a gaseous sample. Raman signals generated by the gaseous sample (i.e., human breath) can be guided and collected effectively for spectral analysis. RESULTS: A Raman-cell based on HC-PCF in the near infrared wavelength range was developed and tested in a single pass forward-scattering mode for different gaseous samples. Raman spectra were obtained successfully from reference gases (hydrogen, oxygen, carbon dioxide gases), ambient air, and a human breath sample. The calculated minimum detectable concentration of this system was ∼15 parts per million by volume, determined by measuring the carbon dioxide concentration in ambient air via the characteristic Raman peaks at 1286 and 1388 cm(-1). CONCLUSIONS: The results of this study were compared to a previous study using HC-PCF to trap industrial gases and backward-scatter 514.5 nm light from them. The authors found that the method presented in this paper has an advantage to enhance the signal-to-noise ratio (SNR). This SNR advantage, coupled with the better transmission of HC-PCF in the near-IR than in the visible wavelengths led to an estimated seven times improvement in the detection sensitivity. The authors' prototype device also demonstrated a 100-fold improvement over a recently reported detection limit of a reflective capillary fiber-based Raman cell for breath analysis. Continued development is underway to increase the detection sensitivity further to reach practical clinical 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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.673

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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