Pesticide Multiresidues in Waters of the Lower Fraser Valley, British Columbia, Canada. Part I. Surface Water
Bibliographic record
Abstract
In the period 2003 to 2005, a study was conducted to determine the occurrence, and spatial and temporal distribution of 78 pesticides in surface waters of the Lower Fraser Valley (LFV) region of British Columbia, Canada. A high resolution gas chromatography/electron impact high resolution mass spectrometry (HRGC/[EI]HRMS) method capable of detecting analytes at the subnanograms per liter level was developed for this study. Samples were collected and analyzed from three reference, five agricultural and two urban sites. Endosulfan sulfate was detected in all samples collected during the study period including the samples from the reference sites. The maximum concentration of a pesticide detected at the reference sites was 0.261 ng L(-1) for beta-endosulfan. Over the study period, the numbers of pesticides detected at the agricultural sites ranged from 22 to 33 of which 20.8 to 40.9% had a 100% detection frequency. At the agricultural sites, the greatest concentration was detected for diazinon (12,500 ng L(-1)), followed by linuron (1050 ng L(-1)) and simazine (896 ng L(-1)). The greatest pesticide concentration observed for the urban sites was 90.4 ng L(-1) for simazine followed by diazinon (5.39 ng L(-1)). With few exceptions, greater concentrations of herbicides were observed for samples collected during spring than for samples collected during fall. Pesticide data presented in this study provide reference levels for future pesticide monitoring programs in the region.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".