Soil—air exchange model of persistent pesticides in the United States cotton belt
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Measurements of organochlorine pesticides (lindane, cis-chlordane [CC], trans-chlordane [TC], trans-nonachlor [TN]), dieldrin, p,p′-dichlorodiphenyldichloroethylene [DDE], and toxaphene) in Alabama, USA, air and soil were used to assess the soil-air equilibrium status and to identify compounds with significant contributions to observed air burdens. Of the compounds tested, p,p′-DDE and toxaphene showed a significant potential for outgasing, followed by dieldrin and trans-nonachlor, which showed moderate outgasing potentials. Lindane, cis-chlordane, and trans-chlordane were near soil-air equilibrium. A fugacity-based, multilayered soil-air exchange model was used to predict temporal trends of chemical in air and soil resulting from reemission of soil residues to a presumed clean atmosphere (maximum emission scenario). Results showed that p,p′-DDE and toxaphene accounted for up to 50% of the observed air burden and that approximately 200 to 600 kg of p,p′-DDE and 3,000 to 11,000 kg of toxaphene are released to the atmosphere each year by soils in Alabama (area = 1.23 × 1011 m2). High annual net fluxes were also predicted for dieldrin and trans-nonachlor (300–1,100 kg and 150–500 kg, respectively), but these only account for up to ∼20% of their observed air burdens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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