Rainfall Patterns Associated with the Oceanic Niño Index in the Colombian Coffee Zone
Bibliographic record
Abstract
<p>Farming is one of the most water-demanding activities in the world. In Colombia, a coffee crop planted with rust-resistant varieties requires between 1500 and 1800 mm of annual rainfall. Crop phenological stages such as flowering and production are determined by the behavior and amount of rainfall. The aim of this study was to evaluate the effect of the Oceanic Niño Index (ONI) on the cumulative rainfall for the Colombian coffee zone. Simple correlations between the Oceanic Niño Index and cumulative monthly rainfall level were analyzed. The correlation coefficient and the p-value were determined for each station analyzed and for each month of the year. The objective is to determine if the ONI could be used in a forecast by analogy—an old but effective method to make decisions in agriculture—and mainly to define adaptation strategies. We found that the relationship between the ONI and cumulative rainfall did not have a homogeneous behavior throughout the country. There are different behaviors, and those depend on the seasons and regions. ONI has a high impact on the rainfall of the dry seasons in the center and sometimes in the south of the country. However in the north, there are no significant effects of this index. It means that other indices should be used to quantify the effect of El Niño and La Niña on the rainfall of the Colombian coffee zone or, on the other way, the use of other climate variability triggers, such as the Pacific Decadal Oscillation or the North Atlantic Oscillation.</p>
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".