Radiocarbon (14C) Analysis of Carbonaceous Aerosols: Revisiting the Existing Analytical Techniques for Isolation of Black Carbon
Bibliographic record
Abstract
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 (14C 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 14C-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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".