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Record W2045347288 · doi:10.1364/oe.19.015244

Monitoring of heparin concentration in serum by Raman spectroscopy within hollow core photonic crystal fiber

2011· article· en· W2045347288 on OpenAlexafffund
Altaf Khetani, Vidhu S. Tiwari, Alaa Harb, Hanan Anis

Bibliographic record

VenueOptics Express · 2011
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsUniversity of Ottawa
FundersOntario Centres of Excellence
KeywordsPhotonic-crystal fiberCuvetteRaman spectroscopyMaterials scienceHeparinPhotonic crystalOptical fiberOpticsPhotonicsOptoelectronicsSIGNAL (programming language)FiberLaserChemistryComputer science

Abstract

fetched live from OpenAlex

The feasibility of using hollow core photonic crystal fiber (HC-PCF) in conjunction with Raman spectroscopy has been explored for real time monitoring of heparin concentration in serum. Heparin is an important blood anti-coagulant whose precise monitoring and controlling in patients undergoing cardiac surgery and dialysis is of utmost importance. Our method of heparin monitoring offers a novel alternative to existing clinical procedures in terms of accuracy, response time and sample volume. The optical design configuration simply involves a 785-nm laser diode whose light is coupled into HC-PCF filled with heparin-serum mixtures. By non-selectively filling HC-PCF, a strong modal field overlap is obtained. Consequently, an enhanced Raman signal (>90 times) is obtained from various heparin-serum mixtures filled HC-PCFs compared to its bulk counterpart (cuvette). The present scheme has the potential to serve as a 'generic biosensing tool' for diagnosing a wide range of biological samples.

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)0.001
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
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.224
Teacher spread0.204 · 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

Citations41
Published2011
Admission routes2
Has abstractyes

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