Startle response and anxiety sensitivity: Subcortical indices of physiologic arousal and fear responding.
Bibliographic record
Abstract
There is a well-established and clinically meaningful relation between the cognitive-affective-based construct of anxiety sensitivity (AS) and risk for the development and maintenance of anxiety psychopathology (B. J. Cox, Fuentes, Borger, & Taylor, 2001). Research findings within this area have revealed mixed results; however, there is evidence to suggest that some individuals with anxiety disorder diagnoses may demonstrate enhanced subcortical arousal (e.g., exaggerated startle response to unexpected, aversive stimuli [A. M. Waters et al., 2008], and deficient prepulse inhibition [PPI; S. Ludewig, Ludewig, Geyer, Hell, & Vollenweider, 2002]), it is presently unclear whether these differences are found within the general population. To address this gap in the extant literature, the current investigation examined the impact of AS on acoustic startle response magnitude and PPI. Results indicated that individuals high and low in AS differ with regard to subcortical measures of arousal, with individuals expressing high levels of AS demonstrating enhanced startle response and deficient PPI. Results are discussed in terms of the role of the cognitive-affective-based factor of AS in the context of physiologic markers for vulnerability for anxiety psychopathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".