NATIONAL INTEGRATED DROUGHT INFORMATION SYSTEM CENTRAL U.S. 2012 DROUGHT ASSESSMENT
Bibliographic record
Abstract
Conditions leading into 2012 gave scant indication of what was to come for a 15-state region in the central United States, extending from Colorado, Wyoming, and North Dakota on the west to Kentucky, Ohio, and Michigan on the east. The drought of 2012 was the first since 1988 that impacted almost the entire Corn Belt. It intensified quickly, catching many by surprise. We hope to learn from this event to help better plan and prepare for the next drought. The full central U.S. 2012 drought assessment, “From too much to too little,” aims to identify the events of 2012 and how they impacted the region, how the drought progressed, and how the states responded. A summary of the year: The winter season of 2011-2012 was strongly influenced by a positive Arctic Oscillation, which correlates with warm winter conditions. Temperatures in January ranked among the top 25 percent of years on record dating to 1895. Precipitation was a mixed bag from month to month, with winter totals running the lowest along the Canadian border and increasing for some of the states farther to the south. Snow totals ranked as the lowest in more than 20 years in the contiguous U.S. The season wrapped up with much warmer than normal temperatures extending across almost the entire region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".