Techniques for Quality Control in Football Field Located in Agricultural Area
Bibliographic record
Abstract
A set of eight sprinklers was evaluated in a soccer field located in the city of Cascavel, Paraná, Brazil, using quality control techniques. The graph X (Shewhart’s individual control card), the EWMA graph (exponentially weighted moving average) and the CUSUM tabular graph (cumulative sum) were used. The system was composed of two parallel lateral lines distanced of 18 meters, containing five sprinklers in each line every 18 meters. The first four sprinklers (area A) and the last four (area B) were evaluated with 25 trials of 10 minutes of irrigation for each area, with the monitoring of climatic effects. For the evaluation of the system, the distribution uniformity coefficient (DU) was used, obtaining in the area A and B the values of 68.72 and 70.0%. This low value can be justified by the high wind velocity during the tests, that varied from 0.57 to 8.5 m s-1. By Shewhart’s control chart, the irrigations of both areas were under control. From the CUSUM chart, only area B was under control. From the EWMA chart, both areas were out of control, being considered the most suitable for evaluation of the system because it detected the small variations in the process.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".