Goodness-of-Fit of Reference Evapotranspiration to Gamma Probability Distribution
Bibliographic record
Abstract
This paper aims to estimate, using the Penman-Monteith method, the probabilities of reference evapotranspiration (ET0) in millimeters, as well as their accumulated values for ten days (decendial), in Mossoró, northeast Brazil. The Meteorological Station of the Federal Rural University of Semi-Arid (UFERSA) provided the daily records of evapotranspiration. The construction of tables based on the approximation of the variable to the Gamma distribution allows the use of data without transformations. The probabilities were estimated with the Gamma distribution at confidence levels of 1% to 95% over the 1970-2007 data period. The results of the chi-square and Kolmogorov-Smirnov tests at 10% probability (p ≥ 0.10) demonstrated the adequacy of the table construction process, providing essential support in the planning of agricultural activities in the region to obtain the maximum benefit from evapotranspiration data. The Gamma probability distribution best described the ET0 for scaling irrigation systems in the county. The maximum daily ET0 for irrigation projects in the Mossoró region is 10 mm, and the cumulative 10-day ET0 averages 80 mm.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".