Prevalence of Thyroid Diseases in Nevada Counties With Respect to Perchlorate in Drinking Water
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perchlorate is well-known to inhibit the uptake of iodine by the thyroid and has been shown to do so at doses in the milligrams-per-day range and higher. Perchlorate has been found in the water supply of Clark County (Las Vegas), Nevada, at 4 to 24 micrograms/L (parts per billion) and may provide exposure dosages in the tens of micrograms per day. An analysis of the Medicaid database from Nevada was undertaken to determine whether an increase in the prevalence of any thyroid disease was associated with that level of perchlorate content. The prevalence of persons being seen for thyroid disease or for specific thyroid diseases (goiter, nodule, thyrotoxicosis, congenital hypothyroidism, acquired hypothyroidism, thyroiditis, and other thyroid disorders) and for thyroid cancer among the Medicaid-eligible population of each county was calculated for the 2-year period 1997 to 1998. The prevalences in Clark County were compared with those in Washoe County (i.e., Reno), the second most populous county in the state, and with those for the rest of the state. There was no evidence of an increased rate of thyroid disease (or of any specific thyroid disease) associated with perchlorate exposure. Generally, the prevalences in the metropolitan parts of the state were lower than for the rest of the state, particularly for acquired hypothyroidism. This analysis found no evidence that perchlorate-containing drinking water at the given level increased the prevalence of acquired hypothyroidism or of any other thyroid condition.
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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) | 0.002 | 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 it