Ethnopedological Studies to Characterize Neosols at the Brazilian Semiarid Region
Bibliographic record
Abstract
The ethnopedological approach to soil characterization presents great challenges, since the understanding of the systems occurs through the knowledge acquired by the man in his coexistence with agroecosystems. The aim of the present research was to characterize the agricultural soils through morphological, physical and chemical analysis, using ethnopedological studies in the ‘Santa Agostinha’ Settlement Project, Caraúbas-RN, Brazil. Five areas were defined for study in the soil/landscape relation: i) area with cashew cultivation; ii) area of pasture; iii) area of crops in consortium; iv) agroforestry; and v) preserved forest, used as the reference. Participatory workshops, exchanges and classifications (from the locals and formal) were carried out with the analysis of the morphological, physical and chemical attributes of the studied soils in the layers of 0.00-0.10, 0.10-0.20 and 0.20-0.30 m. The results of the ethicist classification, based on the attributes evaluation were: Quartzarenic latosol NEOSOL (cashew area); Regolitic euthrofic NEOSOL (pasture area); Ortic quartzarenic fragiudult NEOSOL (intercropping area); typical quartzarenic ortic NEOSOL (agroforestry area and typical hydromorphic quartzarenic NEOSOL that presented a close relation with the emicist classification (from the local people). The observation of the different soil types in the landscape, due to the stratification of the environments, allowed the growers to identify characteristics associated with soil potentials and restrictions and, consequently, the correct management to be adopted. The experiences of local growers in the participatory workshops provided an exchange of popular and scientific knowledge, as well as new perspectives of coexistence with the semiarid.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".