© Author(s) 2008. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics The high Arctic in extreme winters: vortex, temperature, and MLS and ACE-FTS trace gas evolution
Bibliographic record
Abstract
Abstract. The first three Arctic winters of the ACE mis-sion represented two extremes of winter variability: Strato-spheric sudden warmings (SSWs) in 2004 and 2006 were among the strongest, most prolonged on record; 2005 was a record cold winter. Canadian Arctic Atmospheric Chem-istry Experiment (ACE) Validation Campaigns were con-ducted at Eureka (80 ◦ N, 86 ◦ W) during each of these win-ters. New satellite measurements from ACE-Fourier Trans-form Spectrometer (ACE-FTS), Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), and Aura Microwave Limb Sounder (MLS), along with meteorological analyses and Eureka lidar temperatures, are used to detail the meteorology in these winters, to demonstrate its influence on transport, and to provide a context for interpretation of ACE-FTS and validation campaign observations. During the
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.614 | 0.668 |
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".