13 th International Workshop on Greenhouse Gas Measurements from Space - Book of Abstracts
Bibliographic record
Abstract
The 13th International Workshop on Greenhouse Gas Measurements from Space (IWGGMS) will be held on 6-8 June, 2017, at the University of Helsinki in Helsinki, Finland. The workshop is organised by the Finnish Meteorological Institute with support from the University of Helsinki. The workshop gathers together more than 160 scientists from the EU, USA, Japan, China, Australia, Canada, and Russia. This report is the official abstract book of the workshop. Background. Success in space-based global measurement of greenhouse gases, such as carbon dioxide and methane, is critical for advancing the understanding of carbon cycle. The recent developments in observations and in interpreting the data are very promising. Space-based greenhouse gas measurement, however, poses a wide array of challenges, many of which are complex and thus demand close international cooperation. The goal of the workshop is to review the state of the art in remote sensing of CO 2 , CH 4 , and other greenhouse gases from space including the current satellite missions, missions to be launched in the near future, emission hot spots on regional and global scales, process studies and interactions of carbon cycle and climate, pre-flight and on-orbit instrument calibration techniques, retrieval algorithms and uncertainty quantification, validation methods and instrumentation, related ground-based, shipboard, and airborne measurements, and flux inversion from space based measurements. The workshop is part of the programme for the centenary of Finland's independence in 2017. The workshop is also one of the activities arranged by the Finnish Meteorological Institute to support Finland's chairmanship of the Arctic Council, 2017 - 2019. The workshop is sponsored by the Finnish Meteorological Institute, the University of Helsinki, the European Space Agency, the City of Helsinki, the Federation of Finnish Learned Societies, and ABB Inc.
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 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.055 | 0.042 |
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".