Pesticide Residues in Peri-Urban Bovine Milk from India and Risk Assessment: A Multicenter Study
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
Pesticides residue poses serious concerns to human health. The present study was carried out to determine the pesticide residues of peri-urban bovine milk (n = 1183) from five different sites (Bangalore, Bhubaneswar, Guwahati, Ludhiana and Udaipur) in India and dietary exposure risk assessment to adults and children. Pesticide residues were estimated using gas chromatography with flame thermionic and electron capture detectors followed by confirmation on gas chromatography-mass spectrometer. The results noticed the contamination of milk with hexachlorocyclohexane (HCH), dichloro-diphenyl trichloroethane (DDT), endosulfan, cypermethrin, cyhalothrin, permethrin, chlorpyrifos, ethion and profenophos pesticides. The residue levels in some of the milk samples were observed to be higher than the respective maximum residue limits (MRLs) for pesticide. Milk samples contamination was found highest in Bhubaneswar (11.2%) followed by Bangalore (9.3%), Ludhiana (6.9%), Udaipur (6.4%) and Guwahati (6.3%). The dietary risk assessment of pesticides under two scenarios i.e. lower-bound scenario (LB) and upper-bound (UB) revealed that daily intake of pesticides was substantially below the prescribed acceptable daily intake except for fipronil in children at UB. The non-cancer risk by estimation of hazard index (HI) was found to be below the target value of one in adults at all five sites in India. However, for children at the UB level, the HI for lindane, DDT and ethion exceeded the value of one in Ludhiana and Udaipur. Cancer risk for adults was found to be in the recommended range of United States environment protection agency (USEPA), while it exceeded the USEPA values for children.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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