International Consortium for Atmospheric Research on Transport and Transformation (ICARTT): North America to Europe—Overview of the 2004 summer field study
Bibliographic record
Abstract
In the summer of 2004 several separate field programs intensively studied the photochemical, heterogeneous chemical and radiative environment of the troposphere over North America, the North Atlantic Ocean, and western Europe. Previous studies have indicated that the transport of continental emissions, particularly from North America, influences the concentrations of trace species in the troposphere over the North Atlantic and Europe. An international team of scientists, representing over 100 laboratories, collaborated under the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) umbrella to coordinate the separate field programs in order to maximize the resulting advances in our understanding of regional air quality, the transport, chemical transformation and removal of aerosols, ozone, and their precursors during intercontinental transport, and the radiation balance of the troposphere. Participants utilized nine aircraft, one research vessel, several ground‐based sites in North America and the Azores, a network of aerosol‐ozone lidars in Europe, satellites, balloon borne sondes, and routine commercial aircraft measurements. In this special section, the results from a major fraction of those platforms are presented. This overview is aimed at providing operational and logistical information for those platforms, summarizing the principal findings and conclusions that have been drawn from the results, and directing readers to specific papers for further details.
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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 | 0.014 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".