Observer-rated environmental sensitivity and its characterization at behavioral, genetic, and physiological levels
Bibliographic record
Abstract
Abstract This study investigated the psychometric properties of the Highly Sensitive Child-Rating System (HSC-RS), the existence of sensitivity groups, and the characterization of sensitivity at behavioral, genetic, and physiological levels in 541 preschoolers ( M ( SD ) age = 3.56(0.27); 45%male; 87%Caucasian). Temperament, genetic, cortisol, and electroencephalography asymmetry data were collected in subsamples ( n = 94-476). Results showed a reliable observational measure of sensitivity. Confirmatory factor and latent class analysis supported a one-factor solution and three sensitivity groups, that are a low (23.3%), medium (54.2%), and a high (22.5%) sensitivity group. Hierarchical regression analyses showed moderate associations between HSC-RS and observed temperament traits (i.e., behavioral level). In addition, a small negative association between HSC-RS and a genome-wide association study polygenic risk score (GWAS PGS) for Attention Deficit Hyperactivity Disorder was found. No relations with candidate genes, other GWAS PGS phenotypes, and physiological measures were found. Implications of our findings and possible explanations for a lack of these associations are discussed.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".