Bibliographic record
Abstract
The weather systems, cyclones and anticyclones, along with air trajectories and cloud forms, are compared to past studies of the Arctic to assess compatibility of the 4‐month study of FIRE/ACE with past climatologies. The frequency and movement of cyclones (lows) and anticyclones (highs) followed the general eastward and northeastward directions indicated by past studies. Most cyclones (lows) came from eastern Siberia and the Bering Sea to the south and moved north across the Bering Straight or Alaska into the Arctic Ocean. They generally weakened in central pressure as they moved poleward. Anticyclones (highs) were most common in the eastern Beaufort Sea near Canada in June and July, as predicted from previous studies. However, many cyclones and anticyclones moved in westward directions, which is rare in other latitudes. Erratic changes in shape and intensity on a daily basis also were observed. The NOAA National Center for Environmental Prediction (NCEP) analysis generally reflected the SHEBA Ship WMO observations which it used. However, NCEP temperatures were biased warm by 1.0° to 1.5°C in April and early May. In July, when the surface temperatures were at the freezing/thawing point, the NCEP analysis changed to a cold bias of −1.0°C. Dew points had smaller biases except for July where they were biased cold by −1.4°C. Wind speeds had a −2 m/s low bias for the six windiest days. Surface barometric pressures had consistently low biases from −1.2 to −2.8 hPa in all four months. Air parcel historical trajectories were mainly from the south or from local anticyclonic gyres in the Beaufort Sea. Most air came to the SHEBA ship from the North Pacific Ocean or from Alaska and Canada and occasionally from eastern Siberia. Very few trajectories traced back across the pole to Europe and central Asia. Cloud cover was high, as expected, from 69 to 86% of the time. Satellite data also indicate frequent stratus, altostratus, and cirrus clouds (occurring 61% of the time) above the expected boundary layer fog and Arctic stratus clouds.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".