Australian carbon tetrachloride emissions in a global context
Bibliographic record
Abstract
Environmental context Carbon tetrachloride in the background atmosphere is a significant environmental concern, responsible for ~10 % of observed stratospheric ozone depletion. Atmospheric concentrations of CCl4 are higher than expected from currently identified emission sources: largely residual emissions from production, transport and use. Additional sources are required to balance the expected atmospheric destruction of CCl4 and may contribute to a slower-than-expected recovery of the Antarctic ozone ‘hole’. Abstract Global (1978–2012) and Australian (1996–2011) carbon tetrachloride emissions are estimated from atmospheric observations of CCl4 using data from the Advanced Global Atmospheric Gases Experiment (AGAGE) global network, in particular from Cape Grim, Tasmania. Global and Australian emissions are in decline in response to Montreal Protocol restrictions on CCl4 production and consumption for dispersive uses in the developed and developing world. However, atmospheric data-derived emissions are significantly larger than ‘bottom-up’ estimates from direct and indirect CCl4 production, CCl4 transportation and use. Australian CCl4 emissions are not a result of these sources, and the identification of the origin of Australian emissions may provide a clue to the origin of some of these ‘missing’ global sources.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".