Impact of Climate Change and Variability on Wheat and Corn Production in Buenos Aires, Argentina
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
From the Global Historical Climate Network (GHCN-V3), monthly mean summer (DJF) temperature (1856-2012) and total precipitation (1861-2012) are analyzed in correlation with four climate modes and sunspot number to better understand the role of teleconnections on Buenos Aires’ (Argentina) climate. A general increase in temperature and precipitation was observed. Temperature has increased by about 1.8°C and precipitation has increased by about 300 mm in the past century and a half. Indices of Arctic Oscillation (AO), Pacific North American (PNA), Antarctic Oscillation (AAO), and El Nino-Southern Oscillation (ENSO) are evaluated to study their effects on wheat and corn production and export. AO and PNA show strong relationships with precipitation and temperature received. AAO and ENSO show strong negative correlations with precipitation patterns and weak correlations with temperature. Sunspot Number shows a positive correlation with temperature. ENSO phases are strongly linked with the wheat and corn production and export; during El Nino Buenos Aires tends to experience extremely wet summer weather, causing soggy fields and extremely dry summer weather during La Nina causing drought. Both of these conditions result in reducing wheat and corn production and export.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it