Extreme Psycho-Emotional Stress for Kharkivites Caused by Russia-Aggressor Bombardments: Ways to Overcome
Bibliographic record
Abstract
Background: This psychological research, conducted in the first months of the war, was carried out for the first time in world scientific practice. Our aim was to present the missing mathematical-statistical assessment of the emotional response and psycho-physiological state of civilians who, from the first day of the war, were in Kharkiv, constantly under Russian-aggressor fire. Methods: 585 Kharkiv participants were tested using the only possible means accepted during constant rocket attacks and hostilities (visual psychodiagnostics methods). Results: Negative mental manifestations and the disability of Kharkivites to manage their psycho-emotional state have been established. Their evolution has been traced. The time stages of the participants’ states were identified and characterized. Nearly all participants demonstrated intense stress-induced arousal and psycho-emotional incapacity/inability. Psychotrauma also developed among Kharkivites, who constantly monitored military events through social Internet networks. Children were the most susceptible to all severe sensations. Conclusions: The identified conditions are dangerous because they lead to pathological neurological-somatic disorders, psycho-emotional incapacity, or disability due to the stress-induced somatic-physiological destruction of the body. To normalize the psycho-emotional self-awareness and to help the participants get out of a stressful state, various preventive-rehabilitation means were used.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".