Monsoon Season Rain Prediction for the Year 2015 for Telangana, India Based on Telangana’s Historical Rain Data
Bibliographic record
Abstract
In this work the prediction of rain is based on average of two methods. In these methods, historical rain data of Telangana from 1981 to 2012 are selected for projection. These methods take into account the trends in rain pattern also. Among the results are the effects of El Nino and La Nina which for Telangana are not as significant as compared to higher frequencies on annual rainfall basis. The period of these combined effects (El Nino and La Nina) is 10.67 years. The average rainfall of Telangana is 70 centimeters (cms). The normal range of rain varies between the mean+standard deviation as per the Indian Meteorological Department (IMD). The forecast is being made in November 2014 for the Year 2015 that the rain will be normal in the month of June whereas some excess rain will take place in later months as shown in Tables 1 to 5 here. The advantage of this approach is that it gives farmers far more time than they get presently when preliminary predictions are announced by Indian Meteorological Department in April for each monsoon.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".