MétaCan
Menu
Back to cohort
Record W146981277

Application of infrared spectroscopy in the measurement of breath trace compounds: a review

2002· review· en· W146981277 on OpenAlexvenueno aff
Colin D. Mansfield, Henry H. Mantsch, H.N. Rutt

Bibliographic record

VenueNPARC · 2002
Typereview
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsBreath gas analysisBreath testInfrared spectroscopySpectroscopyInfraredAnalytical Chemistry (journal)ChemistryEnvironmental chemistryHelicobacter pyloriMedicineOpticsChromatographyPhysicsGastroenterology
DOInot available

Abstract

fetched live from OpenAlex

The diagnostic potential of human breath has been appreciated for many years, yet the application of infrared spectroscopy for the detection of breath trace compounds is still in its infancy. Few diagnostic or investigative tests involving breath are based upon infrared spectroscopic techniques, its most prominent use to date being the detection of breath ethanol concentration for law enforcement. However, this is destined to change with the emergence of numerous infrared spectroscopic systems designed to measure stable isotope ratios in breath and the substantial market associated with such tests, e.g. the urea breath test for helicobacter pylori. This review article discusses the diagnostic potential and infrared spectroscopy of breath, several of its common features being illustrated with high-resolution spectra. An emphasis is placed on the recent development of instruments to perform isotope ratio breath tests with various approaches described and critiqued. Also the feasibility of using infrared spectroscopy to perform isotopic breath tests other than those based on is explored.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.285
Teacher spread0.246 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicAdvanced Chemical Sensor TechnologiesFrench-language works237,207