1 Applying a dimensional framework to the study of developmental neurotoxicity
Bibliographic record
Abstract
Objective: In recent decades, a large body of evidence has linked prenatal exposure to environmental neurotoxins to adverse intellectual, neurodevelopmental, and psychiatric outcomes in offspring. This evidence has clearly highlighted the widespread impact of neurotoxin exposure on the developing brain; however, it is unclear how and why these exposures alter brain development in a way that appears to increase risk for multiple, seemingly disparate outcomes. Participants and Methods: Shifting our focus from describing links between neurotoxin exposure and symptoms of offspring mental/cognitive problems considered categorically, to investigating how neurotoxins adversely affect domains of functioning known to cut across risk for multiple problems in offspring may be critical to answering these questions. This presentation will discuss how combining research in developmental neurotoxicology with novel systems that take dimensional approaches to understanding emotions, cognition, and behaviour (i.e., the NIHM Research Domain Criteria (RDoC)) may provide a fruitful future research direction for the field. The RDoC framework aims to understand neuropsychological outcomes (i.e., mental health, mental illness, IQ) across major domains of human emotion, cognition, behaviour, and social functioning, rather than within distinct diagnostic categories. Results: Using lead exposure as an example, this presentation will outline a framework for how researchers can use this dimensional approach to develop more specific hypotheses that can reveal how and why neurotoxin exposure increases risk for multiple adverse outcomes and elucidate the mechanisms that may underly these links. Conclusions: Additionally, given that adverse development within domains of functioning can be detected prior to the onset of full-blown diagnoses, this research could enable us to develop more precise, targeted prevention and risk reduction campaigns. Adopting a dimensional framework will provide a more complete picture of the overall impact of prenatal exposure to neurotoxins - critical for informing public health policy.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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 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".