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Record W4405249534 · doi:10.1021/jasms.4c00266

Ultrahigh-Resolution Mass Spectrometry Advances for Biogeochemical Analysis: From Seafloor Sediments to Petroleum and Marine Oil Spills

2024· review· en· W4405249534 on OpenAlexaff
Jagoš R. Radović, Renzo C. Silva

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2024
Typereview
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsBiogeochemical cycleChemistryOil spillMass spectrometryPetroleumSeafloor spreadingEnvironmental chemistryHigh resolutionOceanographyRemote sensingGeologyChromatographyPetroleum engineering

Abstract

fetched live from OpenAlex

This Perspective explores the transformative impact of ultrahigh-resolution mass spectrometry (UHR-MS), particularly Fourier transform ion cyclotron resonance (FT-ICR-MS), in the characterization of complex environmental and petroleum samples. UHR-MS has significantly advanced our ability to identify molecular formulas in complex mixtures, revolutionizing the study of biogeochemical processes and organic matter evolution on wide time scales. We start by briefly reviewing the main technological advances of UHR-MS in the context of petroleum and environmental applications, highlighting some of the challenges of the technology such as quantitation and structural identification. We then showcase a selection of impactful applications published in the last 20+ years. In the field of environmental lipidomics, high-resolution analysis of lipids in sediments enables multiproxy studies and provides novel insights into past environmental conditions. UHR-MS has also facilitated the characterization of kerogen, a complex, poorly soluble mixture formed from sedimented organic matter over geological time scales, and the identification of polar compounds within its fractions. In petroleum (geo)chemistry, UHR-MS has enabled the identification of biomarkers such as petroporphyrins, asphaltenes, and high-molecular-weight naphthenic acids, shedding light on the molecular complexity of crude oil. The application of UHR-MS in oil spill science has revealed significant molecular transformations during weathering processes, such as photo-oxidation, which are crucial for assessing the environmental impact of past spills and improving the preparedness for future spills. These advancements underscore the role of this maturing analytical technology in deepening our understanding of geochemical processes and biogeochemical cycles, highlighting its potential for future research directions in organic geochemistry.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.002
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.311
Teacher spread0.297 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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