Application of 700 Millibar Synotic Climatology to Drought Analysis
Bibliographic record
Abstract
Large areas of the earth's surface experience occasional climatic fluctuations. Such fluctuations, integral to the weather system, often lead to drought or flood, and this influences crop production and commodity prices. Drought is a contributor to economic, social, and, on occasion, even political instability in both commercial and subsistence agricultural economics. Particularly affected are areas such as India, China, parts of Europe, and the American Great Plains which include the Canadian "Prairies". Because of its dominantly agricultural economy, and because of its location well within a zone of frequent drought, the Canadian Prairies section has been selected for study. Past studies on Canadian droughts put emphasis on drought patterns by using Thornthwaite moisture indices' but in so doing have expressed the effects rather than the causes of droughts. The objective of this paper is to examine the summer droughts in the Canadian Prairies by using synoptic climatological approach2• Recent studies by meteorologists and climatologists indicate the usefulness of synoptic climatology to analyze climatic problems. 3 However, their application to drought analysis is lackin
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.000 |
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".