Lack of a Relation Between Human Neonatal Thyroxine and Pediatric Neurobehavioral Disorders
Bibliographic record
Abstract
The growth and differentiation of the central nervous system are closely related to the presence of iodine and thyroid hormones. It has been hypothesized that neurobehavioral disabilities of childhood, such as attention deficit hyperactivity disorder (ADHD), learning disorders, and autism can be attributed to fetal thyroidal endocrine disruption in utero. To determine whether there is an association between neonatal thyroid status and a subsequent diagnosis of a neurobehavioral disability, neonatal thyroxine (T(4)) levels have been used as the indicator of the presence of intrauterine thyroidal dysfunction. Neonatal T(4) levels were obtained from the neonatal hypothyroidism screening program. All cases were diagnosed at medical school diagnostic clinics, the diagnostic categories being ADHD, autism spectrum disorder, behavioral disorder, cognitive disorder, developmental delay, emotional disorder, learning disability, and speech/language disorder. Conditional logistic regression analysis was performed for each clinical condition. Odds ratios for the conditions ranged from 0.92 to 1.13 with p values ranging between 0.19 and 0.84. No significant differences were detected between neonatal T(4) values of the cases and the controls for any of the neurobehavioral conditions. All neonatal T(4) values were within normal ranges. The data provide no evidence to suggest that intrauterine thyroid status as reflected by the neonatal T(4) values had an impact on the neurologic disorders diagnosed in childhood.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".