Smoke stops firefighting from the air over western U.S.
Bibliographic record
Abstract
Smoke from huge wildfires burning in the west has shut down firefighting efforts from the sky. Washington Department of Natural Resources helicopter pilot Ken Johnson says he's just waiting for the next chance to get up in the air... With resources stretched thin...firefighters from Australia and New Zealand are on hand helping with the Okanogan fire burning near the border with Canada. While 200 U-S Army troops are helping with a fire about 150 miles east of Portland. Johnson says he and his chopper can only do so much...and the extra manpower is a big help... Meanwhile in upstate Republic, Washington, Sue Baldwin has set up sprinklers on the roof of her real estate business... She says so far...this has been an intense wildfire season... More than 11,600 acres have been burned so far by fires in Washington, California, Montana and Idaho. Fire crews are counting on cooler weather and a chance for a little rain to help get some of the flames under control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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; both teacher heads agree on what is shown here.
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".