Identification of Areas Irrigated by Central Pivot in the State of Goiás, Brazil
Why this work is in the frame
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Bibliographic record
Abstract
The state of Goiás, Brazil offers a territorial division with well-defined areas in terms of water capacity. The water found in these dividers is used in various agriculture segments. There were identified in the Hydrographic Basins in the State, areas irrigated by central pivots used in irrigated agriculture that is developing very fast and this can become a problem if a control is not done. This study aimed to collect data, identify and quantify the distribution of irrigation systems of the central pivot type licensed and operating in a spatial format in the Hydrographic Basins in the State of Goiás. It raised digital data and physical media in order to understand how these were able to characterize the research area. It analyzed the maps, existing in the database of the State through digital (SIEG-State System of Statistics and Geographic Information of Goiás). With the use of AutoCAD programs, version 2018, there was utilized the geographic information plataform QGIS 2.14.19 with GRASS 7.2.1 has organized thematic maps of hydrographs and pivots. This material provided the possibility of compiling the fundamental data to structure the information that supports the descriptive dynamics of the number of pivots even in separate basins. This information analyzed and compared to other publications about pivots in Goiás contributed to the formation and elaboration of a data model for the year 2017. In the State of Goiás, Brazil, there is a total of 3,223 central pivot type equipment in operation irrigating an area corresponding to 234,226.12 hectares.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it