Duplicate Sampling of Surface Films and Associated Pond Water for Herbicides
Bibliographic record
Abstract
Abstract This paper describes the variability of herbicide concentrations in the surface film and subsurface water of small, artificial prairie ponds (dugouts) as determined by comparing duplicate samples. Duplicate surface film samples were collected using a horizontally held glass plate and washed into a collection bottle with dichloromethane. Subsurface water samples were collected by plunging bottles into the pond to a depth of approximately 0.25 m. The samples were collected weekly from two dugouts in 1989 and from one dugout in 1990. Samples were analyzed for 2,4‐D, dicamba, bromoxynil, MCPA, triallate, trifluralin, and diclofop using a gas chromatograph interfaced with a mass selective detector. The average variability of the surface film samples was ±40% of the average of the pair with a confidence interval of 97% ( p = 0.05). The average variability of the subsurface water samples was ±25% of the average of the pair with a confidence interval of 71% ( p = 0.05). Possible reasons for the variability, including the nonhomogeneity of the surface film, are discussed.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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 teacher head, 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".