ELISA and GC-MS as Teaching Tools in the Undergraduate Environmental Analytical Chemistry Laboratory
Bibliographic record
Abstract
An undergraduate experiment for the analysis of potential water pollutants is described. Students are exposed to two complementary techniques, ELISA and GC-MS, for the analysis of a water sample containing atrazine, desethylatrazine, and simazine. Atrazine was chosen as the target analyte because of its wide usage in North America and its utility for students to predict environmental degradation products. The water sample is concentrated using solid-phase extraction for GC-MS, or diluted and analyzed using a competitive ELISA test kit for atrazine. The nature of the water sample is such that students generally find that ELISA gives an artificially high value for the concentration of atrazine. Students gain an appreciation for problems associated with measuring pollutants in the aqueous environment: sensitivity, accuracy, precision, and ease of analysis. This undergraduate laboratory provides an opportunity for students to learn several new analysis and sample preparation techniques and to critically evaluate these methods in terms of when they are most useful.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".