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Record W4285394546 · doi:10.3389/fenvs.2022.907467

Radiocarbon (14C) Analysis of Carbonaceous Aerosols: Revisiting the Existing Analytical Techniques for Isolation of Black Carbon

2022· article· en· W4285394546 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.

Bibliographic record

VenueFrontiers in Environmental Science · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEnvironmental scienceAir quality indexAir pollutionRadiocarbon datingGreenhouse gasClimate changeCarbon blackIsotope analysisWork (physics)PollutionEnvironmental resource managementEnvironmental planningMeteorologyChemistryGeographyEngineeringGeology

Abstract

fetched live from OpenAlex

Air pollution, a complex cocktail of different components, exerts an influence on climate/human; health both locally and away from source regions. The issue of air pollution is often closely linked; to carbonaceous aerosols, the assessment of climate/air quality/health impact of which remains associated with large uncertainties. Black carbon (BC)—a product of incomplete combustion—is a potent climate warming agent and one of the central components to this issue. An accurate; knowledge of BC emitting sources is necessary for devising appropriate mitigation strategies and; policies to reduce the associated climate/environmental burden. The radiocarbon isotope ( 14 C or carbon-14) fingerprinting allows for an unambiguous and quantitative constraining of the BC sources and is therefore a well-popularized method. Here, we review the existing analytical techniques for the isolation of BC from a filter matrix for conducting 14 C-based investigations. This work summarizes the protocols in use, provides an overarching perspective on the state-of- the-art and recommendations for certain aspects of future method development.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.220
Teacher spread0.209 · 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