Heavy Metals in Agricultural Soils of San Francisco de Macorís and La Vega, Dominican Republic
Bibliographic record
Abstract
In Dominican Republic exists cultive larges fields of various agricultural rubles. The largest extensions are rice, banana and cocoa; these are located in the Cibao Valley. In the eastern, southwestern, and a small area in the north of the country, sugar cane is cultivated. Heavy metals are found in many of these soils that could be affecting the quality of agricultural products or production. The levels of Cr, Ni, Zn, Cu, Cd, As, Hg and Pb, determined by X-ray fluorescence spectroscopy, in soils collected in two cultivation areas of Rice de La Vega and San Francisco de Macoris (SFM) have been compared with the NOAA-USEPA Canadian Agricultural Soil and Sediment Guide (CEQGs) (SQuiRTs Table). The levels of Cr and Ni in La Vega exceeded the threshold effects levels (TEL), and the probable effects levels (PEL). Pb levels in the La Vega area were higher than in SFM. In general, these metals are found in the La Vega area in higher concentrations than in SFM, exceeding PEL and TEL.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".