Development of an Enzyme-Linked Immunosorbent Assay for the Detection of Dicamba
Bibliographic record
Abstract
A competitive indirect enzyme-linked immunosorbent assay (CI-ELISA) was developed to quantitate the herbicide dicamba (3,6-dichloro-2-methoxybenzoic acid) in water. The CI-ELISA has a detection limit of 2.3 microg L(-1) and a linear working range of 10--10000 microg L(-1) with an IC(50) value of 195 microg L(-1). The dicamba polyclonal antisera did not cross-react with a number of other herbicides tested but did cross-react with a dicamba metabolite, 5-hydroxydicamba, and structurally related chlorobenzoic acids. The assay was used to estimate quantitatively dicamba concentrations in water samples. Water samples were analyzed directly, and no sample preparation was required. To improve detection limits, a C(18) (reversed phase) column concentration step was devised prior to analysis, and the detection limits were increased by at least by 10-fold. After the sample preconcentration, the detection limit, IC(50), and linear working range were 0.23, 19.5, and 5-200 microg L(-1), respectively. The CI-ELISA estimations in water correlated well with those from gas chromatography-mass spectrometry (GC-MS) analysis (r(2) = 0.9991). This assay contributes to reducing laboratory costs associated with the conventional GC-MS residue analysis techniques for the quantitation of dicamba in water.
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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 | 0.000 | 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 | 0.000 |
| 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 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".