1231 – From Temperament To Psychopathology: An Etiological Continuum Hypothesis
Bibliographic record
Abstract
Temperament is viewed here as referring to biologically based individual differences with main links to endocrinal-limbic regulation and to the morphology of the nervous system. Findings in psychophysiology, neuropsychology, mood disorders and personality disorders are compared to the traits described within the Functional Ensemble of Temperament (FET) model. FET consists of 12 components, which reflect the regulation of behaviour in four perspectives of functional tasks: dynamical aspects of tasks (energetic, lability and directionality), probabilistic (known task vs. uncertain), activity-specific (physical vs. verbalsocial vs. mental) and emergency aspects (involvement of emotional regulation). This review of the author's studies and the existing literature will argue for the contribution of imbalances in systems of opioid receptors, neurotransmitters, neuropeptides, and hormons, providing etiological linkages among temperament traits, mood and personality disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".