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Record W4410436426 · doi:10.1021/acsomega.5c02123

Beyond Accelerator Mass Spectrometry: Recent Developments in All-Optical Measurements of Radioisotope Carbon

2025· review· en· W4410436426 on OpenAlexaff
Gordon H. K. Duddy, Lucas M. Morrison, Jon P. Camden

Bibliographic record

VenueACS Omega · 2025
Typereview
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsImperial Oil (Canada)
FundersNational Science Foundation
KeywordsAccelerator mass spectrometryMass spectrometryRadiochemistryCarbon fibersNuclear physicsChemistryMaterials sciencePhysicsChromatography

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide The environmental impact of non-renewable energy has come under scrutiny, prompting investments in carbon management strategies like renewable fuels. The presence of radiocarbon in biofuel blends can validate their composition for government regulators and quality control. However, such measurements are challenging and costly, requiring accelerator mass spectrometry (AMS) or liquid scintillation counting (LSC), which necessitate extensive preparation, expensive equipment, and highly trained personnel. Significant advancements have been recently made in developing optical methodologies capable of detecting 14 C at part per quadrillion sensitivity, with a smaller footprint, simpler sample preparation, and reduced cost. This review critically examines the benefits and limitations of direct absorption, cavity ringdown spectroscopy, intracavity optogalvanic spectroscopy, and photoacoustic spectroscopy as optical radiocarbon detection systems that may replace accelerator mass spectrometry as the primary gold standard methodology available.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.059
GPT teacher head0.330
Teacher spread0.271 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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