Investigation into Endocrine Disruptors At the City of Oklahoma Citys Selected Wastewater Treatment Plants
Bibliographic record
Abstract
Oklahoma City's three largest WWTPs were evaluated for potential vulnerability to EDCs and pharmaceutical pollutants in the influent wastewater streams. A list of candidates for screening was compiled based on potential for occurrence and analytical capability for testing the compounds of interest. Several of the compounds detected include: acetaminophen, caffeine, gemfibrozil (a cholesterol regulator), triclosan (antibacterial agent), sulfamethoxazole (a sulfa-based antibiotic), carbamazepine (anti-anxiety mood stabilizer), progesterone (female hormone), iopromide (iodinated contrast media), trimethoprim (antibiotic), and 4-methylphenol (intermediate organic widely used in industrial processes). In addition to the list of compounds, information regarding common usage, industrial application, and selected chemical properties is provided. The data presented in this report represent a single sampling event, or snapshot, of WWTP water quality. The findings are from a single point in time and do not include influence from factors such as seasonal variation of flow in to the WWTP, changes in treatment (i.e. chlorination/dechlorination), and application of pesticides, fertilizers, etc. by both residential and agricultural users. Concentrations in the plant effluent imply the need for further work to more fully characterize seasonal variability. Few conclusions can be reliably formed without further testing, however, it is clear that some chemicals do appear to pass-through the treatment process at some level. More work needs to be performed to gain a better understanding of the potential impacts to Oklahoma City source waters and natural waters of the state. Although the City's WWTPs do not discharge to any of the City's drinking water sources, additional work should be conducted to determine potential impact from upstream activities on the North Canadian River.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".