Autotraining using sustainable digital technologies: myth or reality
Bibliographic record
Abstract
This study aimed to analyze the possibilities that modern digital technologies offer to the fields of health, psychotherapy, psychology and self-help. A review of various studies in the field of digital medicine with statistical data was conducted. The conclusions that researchers from different countries came to were similar: digital health applications are a practical solution that can be used to improve mental and psychological health. Moreover, digital psychotherapy can serve as a preventive tool to avert the development of mental disorders, increase the ability to deal with stress and mental problems, grow self-confidence, and more. The results of a study that was carried out using a Russian multimedia tool Master Kit are discussed. After using the program for three months, its users advanced in their ability to create an image of the desired outcome (a goal) and develop a plan to reach it. There is a noticeable difference in how goal-oriented the users became and their ability to independently self-train. Experimental data suggest that the tool can be effectively used to form and transform personal beliefs through a self-training format. More than half of the subjects talked about their satisfaction with the method, and more than one-quarter of them noted that their expectations from working with the program were fully satisfied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".