Hg Physicochemical Processes at Atmospheric Interfaces, in the Age of Climate Change
Bibliographic record
Abstract
Atmospheric interfaces, such as aerosols, clouds, and air/wate/snowice/soil/vegetation/built surfaces, play exciting roles from affecting the plenatary energy budget and climate change, to photochemistry, catlysis, and biogeochemical cycling.Although, there are signficant advances in understanding physicochemical and biogeochemical process in atmospheric interfaces, there is much unknown, As a result, the IPCC (2018) has idenfied the the major uncertainty in the domain of climate change to be aerosol and aerosol cloud interactions The WHO (2018) has also pointed out that air pollution, particulalry smaller aerosols, are the cause for premature death of ~ 8 million human beings every year, globally.Indeed, some physicochemical processes such as size, hygroscopicity, configuration, number density, contact angle, surface photochemistry, which are understaood to be gap-of-knowledge in climate change, are also kely gap-ofknowldege in toxicocological and health studies.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".